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Interactive online version:
Slideshow:
Slideshow:
A real-world demo of data analysis¶
topics covered:¶
- import data with correct data types
- merge/combine
DataFrames for easier analysis- how to read/understand technical manuals? differences between manual and tutorial
- utilise examples
- get ensembles using
GroupBy-related functions - understand the “notorious”
matplotlib-based plotting: http://pbpython.com/effective-matplotlib.html - plotting like a pro using
seaborn- understand the desirable data format for using
seaborn - some useful plot types
- beautify your plots
- understand the desirable data format for using
practical part¶
[1]:
from pathlib import Path
import pandas as pd
import numpy as np
import matplotlib.pyplot as plt
import seaborn as sns
%matplotlib inline
[2]:
path_data_dir=Path('../data')
[3]:
list(path_data_dir.glob('*csv'))
[3]:
[PosixPath('../data/WP_stable_rawdata.csv'),
PosixPath('../data/EC_rawdata.csv'),
PosixPath('../data/UoR_Data_EC.csv'),
PosixPath('../data/PM_rawdata.csv'),
PosixPath('../data/UoR_Data_5min.csv'),
PosixPath('../data/WP_unstable_rawdata.csv')]
[4]:
path_data_5min=path_data_dir/'UoR_Data_5min.csv'
path_data_EC=path_data_dir/'UoR_Data_EC.csv'
[5]:
list_dates= pd.date_range('2018 09 01','2018 10 01')
list_start=list_dates[:-1]
list_end=list_dates[1:]
[6]:
url_data_5min_template = (
'https://metdata.reading.ac.uk/ext/dataset/'
'5min_Level2/get_data'
'?token=3bab029493'
'&start_date={start:%Y-%m-%d-%H:%M:%S%z}'
'&end_date={end:%Y-%m-%d-%H:%M:%S%z}'
'&var=TSoil100&var=TSoil10&var=TSoil20&var=TSoil30&var=TSoil50&var=TSoil5&var=Tsoil&var=Tconc&var=Tdew_der&var=VP_der&var=Twet_der&var=Td&var=Tgrass&var=Tw&var=RH&var=U10max_der&var=U10run_der&var=Dirn10&var=U10&var=U2run_der&var=U5max_der&var=U5run_der&var=Dirn5&var=U5&var=Sdur&var=Sg_accum_der&var=Sdur_accum_der&var=CNR4T&var=Sd&var=Sb&var=Sg&var=G&var=Ldw&var=Ldw(uc)&var=Luw&var=Luw(uc)&var=Rn&var=Sb(csd3)&var=Sdw&var=Suw&var=Pmsl&var=P&var=Rain&var=Rain_accum_der'
'&missing=NaN&data_format=csv')
list_url_data_5min=[url_data_5min_template.format(start=start,end=end) for start, end in zip(list_start,list_end)]
[7]:
rawdata_5min=pd.concat([pd.read_csv(url,header=[0, 1]) for url in list_url_data_5min])
[8]:
data_5min=rawdata_5min.set_index(('TimeStamp','timestamp'))
[9]:
data_5min.head()
[9]:
| TSoil100 | TSoil10 | TSoil20 | TSoil30 | TSoil50 | TSoil5 | Tsoil | Tconc | Tdew_der | VP_der | ... | Luw | Luw(uc) | Rn | Sb(csd3) | Sdw | Suw | Pmsl | P | Rain | Rain_accum_der | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| degC | degC | degC | degC | degC | degC | degC | degC | degC | hPa | ... | W/m^2 | W/m^2 | W/m^2 | W/m^2 | W/m^2 | W/m^2 | hPa | hPa | mm | mm | |
| (TimeStamp, timestamp) | |||||||||||||||||||||
| 2018-09-01 00:05:00 | 16.95 | 17.44 | 17.56 | 17.50 | 16.83 | 16.99 | 10.51 | 13.43 | 10.21 | 12.45 | ... | 347.26 | -13.28 | -37.87 | -4.8 | -0.84 | 2.10 | 1024.69 | 1016.61 | 0.0 | 0.0 |
| 2018-09-01 00:10:00 | 16.96 | 17.42 | 17.56 | 17.51 | 16.83 | 16.96 | 10.65 | 13.54 | 10.14 | 12.40 | ... | 346.82 | -13.61 | -35.03 | -4.7 | -2.27 | 2.26 | 1024.64 | 1016.55 | 0.0 | 0.0 |
| 2018-09-01 00:15:00 | 16.96 | 17.39 | 17.55 | 17.50 | 16.84 | 16.93 | 10.52 | 13.38 | 9.94 | 12.24 | ... | 346.18 | -13.35 | -36.05 | -4.7 | -2.03 | 1.30 | 1024.61 | 1016.51 | 0.0 | 0.0 |
| 2018-09-01 00:20:00 | 16.95 | 17.37 | 17.54 | 17.51 | 16.84 | 16.89 | 10.30 | 13.08 | 10.40 | 12.61 | ... | 346.56 | -13.80 | -35.92 | -4.9 | -0.40 | 3.46 | 1024.57 | 1016.48 | 0.0 | 0.0 |
| 2018-09-01 00:25:00 | 16.95 | 17.35 | 17.53 | 17.50 | 16.84 | 16.86 | 10.36 | 13.12 | 10.18 | 12.43 | ... | 346.42 | -13.76 | -41.32 | -4.7 | -1.73 | 1.22 | 1024.55 | 1016.45 | 0.0 | 0.0 |
5 rows × 44 columns
[10]:
url_data_EC_template = (
'https://metdata.reading.ac.uk/ext/dataset/'
'eddy_cov/get_data'
'?token=3bab029493'
'&start_date={start:%Y-%m-%d-%H:%M:%S%z}'
'&end_date={end:%Y-%m-%d-%H:%M:%S%z}'
'&var=WS&var=dir&var=L&var=zL&var=C_CO2&var=cov_uv&var=cov_uw&var=cov_vw&var=ustar&var=Tsonic&var=nSamples&var=q&var=sd_C_CO2&var=sd_Tsonic&var=sd_q&var=sd_u&var=sd_v&var=sd_w&var=F_CO2&var=Q_E&var=Q_H&'
'&missing=NaN&data_format=csv')
list_url_data_EC=[url_data_EC_template.format(start=start,end=end) for start, end in zip(list_start,list_end)]
[ ]:
[22]:
rawdata_EC.head()
[22]:
| TimeStamp | WS | dir | L | zL | C_CO2 | cov_uv | cov_uw | cov_vw | ustar | ... | q | sd_C_CO2 | sd_Tsonic | sd_q | sd_u | sd_v | sd_w | F_CO2 | Q_E | Q_H | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 0 | timestamp | m.s-1 | degree | m | dimensionless | mmol.m-3 | m2.s-2 | m2.s-2 | m2.s-2 | m.s-1 | ... | kg.kg-1 | mmol.m-3 | Celsius | kg.kg-1 | m.s-1 | m.s-1 | m-2/3 | umol.m-2.s-1 | W.m-2 | W.m-2 |
| 1 | 2018-09-01 00:30:00 | 0.195 | 202.3 | 4.584 | 0.63269 | NaN | 0.0171 | 0.00236 | 0.0002 | 0.0487 | ... | NaN | NaN | 0.346 | NaN | 0.227 | 0.1765 | 0.0505 | NaN | NaN | -4.236 |
| 2 | 2018-09-01 01:00:00 | 0.1427 | 155.7 | -10.262 | -0.28259 | NaN | -0.018 | 0.00297 | 0.000366 | 0.0547 | ... | NaN | NaN | 0.376 | NaN | 0.176 | 0.2768 | 0.0419 | NaN | NaN | 2.717 |
| 3 | 2018-09-01 01:30:00 | 0.1527 | 264.8 | 0.834 | 3.47569 | 0.000671 | -0.00245 | 0.000465 | -2.65e-06 | 0.0216 | ... | NaN | 1.16e-05 | 0.309 | NaN | 0.129 | 0.1478 | 0.0237 | 0.2776 | NaN | -1.995 |
| 4 | 2018-09-01 02:00:00 | 0.1191 | 155.8 | -20.08 | -0.14442 | 0.000701 | -0.00874 | -0.00655 | -0.00253 | 0.0838 | ... | NaN | 1.51e-05 | 0.256 | NaN | 0.334 | 0.2337 | 0.0492 | -9.6545 | NaN | 4.82 |
5 rows × 22 columns
[11]:
rawdata_EC=pd.concat([pd.read_csv(url) for url in list_url_data_EC])
[12]:
data_EC=rawdata_EC.drop_duplicates().T.set_index(0,append=True).T.set_index(('TimeStamp','timestamp'))
[13]:
data_5min.index=data_5min.index.astype(np.datetime64)
[14]:
data_30min=data_5min.resample('30T').mean()
[15]:
data_EC.index=data_EC.index.astype(np.datetime64)
[16]:
data_ana=pd.concat([data_30min,data_EC],axis=1)
[17]:
data_ana.loc[:,['Rn','Q_H','Q_E','G']].plot()
[17]:
<matplotlib.axes._subplots.AxesSubplot at 0x115b91f98>
[18]:
data_ana.columns.levels[0]
[18]:
Index(['CNR4T', 'C_CO2', 'Dirn10', 'Dirn5', 'F_CO2', 'G', 'L', 'Ldw',
'Ldw(uc)', 'Luw', 'Luw(uc)', 'P', 'Pmsl', 'Q_E', 'Q_H', 'RH', 'Rain',
'Rain_accum_der', 'Rn', 'Sb', 'Sb(csd3)', 'Sd', 'Sdur',
'Sdur_accum_der', 'Sdw', 'Sg', 'Sg_accum_der', 'Suw', 'TSoil10',
'TSoil100', 'TSoil20', 'TSoil30', 'TSoil5', 'TSoil50', 'Tconc', 'Td',
'Tdew_der', 'Tgrass', 'Tsoil', 'Tsonic', 'Tw', 'Twet_der', 'U10',
'U10max_der', 'U10run_der', 'U2run_der', 'U5', 'U5max_der', 'U5run_der',
'VP_der', 'WS', 'cov_uv', 'cov_uw', 'cov_vw', 'dir', 'nSamples', 'q',
'sd_C_CO2', 'sd_Tsonic', 'sd_q', 'sd_u', 'sd_v', 'sd_w', 'ustar', 'zL'],
dtype='object')
[23]:
# data_ana.Q_H.values
data_ana.Q_H.astype(float).plot()
[23]:
<matplotlib.axes._subplots.AxesSubplot at 0x11858c8d0>
[24]:
data_ana.loc[:,['Rn','Q_H','Q_E','G']].astype(float).plot()
[24]:
<matplotlib.axes._subplots.AxesSubplot at 0x1187b2b38>
[29]:
data_ana.index
[29]:
DatetimeIndex(['2018-09-01 00:00:00', '2018-09-01 00:30:00',
'2018-09-01 01:00:00', '2018-09-01 01:30:00',
'2018-09-01 02:00:00', '2018-09-01 02:30:00',
'2018-09-01 03:00:00', '2018-09-01 03:30:00',
'2018-09-01 04:00:00', '2018-09-01 04:30:00',
...
'2018-09-30 19:30:00', '2018-09-30 20:00:00',
'2018-09-30 20:30:00', '2018-09-30 21:00:00',
'2018-09-30 21:30:00', '2018-09-30 22:00:00',
'2018-09-30 22:30:00', '2018-09-30 23:00:00',
'2018-09-30 23:30:00', '2018-10-01 00:00:00'],
dtype='datetime64[ns]', name=('TimeStamp', 'timestamp'), length=1441, freq='30T')
[28]:
grp_hr_min.groups
[28]:
{(0, 0): DatetimeIndex(['2018-09-01', '2018-09-02', '2018-09-03', '2018-09-04',
'2018-09-05', '2018-09-06', '2018-09-07', '2018-09-08',
'2018-09-09', '2018-09-10', '2018-09-11', '2018-09-12',
'2018-09-13', '2018-09-14', '2018-09-15', '2018-09-16',
'2018-09-17', '2018-09-18', '2018-09-19', '2018-09-20',
'2018-09-21', '2018-09-22', '2018-09-23', '2018-09-24',
'2018-09-25', '2018-09-26', '2018-09-27', '2018-09-28',
'2018-09-29', '2018-09-30', '2018-10-01'],
dtype='datetime64[ns]', name=('TimeStamp', 'timestamp'), freq='1440T'),
(0, 30): DatetimeIndex(['2018-09-01 00:30:00', '2018-09-02 00:30:00',
'2018-09-03 00:30:00', '2018-09-04 00:30:00',
'2018-09-05 00:30:00', '2018-09-06 00:30:00',
'2018-09-07 00:30:00', '2018-09-08 00:30:00',
'2018-09-09 00:30:00', '2018-09-10 00:30:00',
'2018-09-11 00:30:00', '2018-09-12 00:30:00',
'2018-09-13 00:30:00', '2018-09-14 00:30:00',
'2018-09-15 00:30:00', '2018-09-16 00:30:00',
'2018-09-17 00:30:00', '2018-09-18 00:30:00',
'2018-09-19 00:30:00', '2018-09-20 00:30:00',
'2018-09-21 00:30:00', '2018-09-22 00:30:00',
'2018-09-23 00:30:00', '2018-09-24 00:30:00',
'2018-09-25 00:30:00', '2018-09-26 00:30:00',
'2018-09-27 00:30:00', '2018-09-28 00:30:00',
'2018-09-29 00:30:00', '2018-09-30 00:30:00'],
dtype='datetime64[ns]', name=('TimeStamp', 'timestamp'), freq='1440T'),
(1, 0): DatetimeIndex(['2018-09-01 01:00:00', '2018-09-02 01:00:00',
'2018-09-03 01:00:00', '2018-09-04 01:00:00',
'2018-09-05 01:00:00', '2018-09-06 01:00:00',
'2018-09-07 01:00:00', '2018-09-08 01:00:00',
'2018-09-09 01:00:00', '2018-09-10 01:00:00',
'2018-09-11 01:00:00', '2018-09-12 01:00:00',
'2018-09-13 01:00:00', '2018-09-14 01:00:00',
'2018-09-15 01:00:00', '2018-09-16 01:00:00',
'2018-09-17 01:00:00', '2018-09-18 01:00:00',
'2018-09-19 01:00:00', '2018-09-20 01:00:00',
'2018-09-21 01:00:00', '2018-09-22 01:00:00',
'2018-09-23 01:00:00', '2018-09-24 01:00:00',
'2018-09-25 01:00:00', '2018-09-26 01:00:00',
'2018-09-27 01:00:00', '2018-09-28 01:00:00',
'2018-09-29 01:00:00', '2018-09-30 01:00:00'],
dtype='datetime64[ns]', name=('TimeStamp', 'timestamp'), freq='1440T'),
(1, 30): DatetimeIndex(['2018-09-01 01:30:00', '2018-09-02 01:30:00',
'2018-09-03 01:30:00', '2018-09-04 01:30:00',
'2018-09-05 01:30:00', '2018-09-06 01:30:00',
'2018-09-07 01:30:00', '2018-09-08 01:30:00',
'2018-09-09 01:30:00', '2018-09-10 01:30:00',
'2018-09-11 01:30:00', '2018-09-12 01:30:00',
'2018-09-13 01:30:00', '2018-09-14 01:30:00',
'2018-09-15 01:30:00', '2018-09-16 01:30:00',
'2018-09-17 01:30:00', '2018-09-18 01:30:00',
'2018-09-19 01:30:00', '2018-09-20 01:30:00',
'2018-09-21 01:30:00', '2018-09-22 01:30:00',
'2018-09-23 01:30:00', '2018-09-24 01:30:00',
'2018-09-25 01:30:00', '2018-09-26 01:30:00',
'2018-09-27 01:30:00', '2018-09-28 01:30:00',
'2018-09-29 01:30:00', '2018-09-30 01:30:00'],
dtype='datetime64[ns]', name=('TimeStamp', 'timestamp'), freq='1440T'),
(2, 0): DatetimeIndex(['2018-09-01 02:00:00', '2018-09-02 02:00:00',
'2018-09-03 02:00:00', '2018-09-04 02:00:00',
'2018-09-05 02:00:00', '2018-09-06 02:00:00',
'2018-09-07 02:00:00', '2018-09-08 02:00:00',
'2018-09-09 02:00:00', '2018-09-10 02:00:00',
'2018-09-11 02:00:00', '2018-09-12 02:00:00',
'2018-09-13 02:00:00', '2018-09-14 02:00:00',
'2018-09-15 02:00:00', '2018-09-16 02:00:00',
'2018-09-17 02:00:00', '2018-09-18 02:00:00',
'2018-09-19 02:00:00', '2018-09-20 02:00:00',
'2018-09-21 02:00:00', '2018-09-22 02:00:00',
'2018-09-23 02:00:00', '2018-09-24 02:00:00',
'2018-09-25 02:00:00', '2018-09-26 02:00:00',
'2018-09-27 02:00:00', '2018-09-28 02:00:00',
'2018-09-29 02:00:00', '2018-09-30 02:00:00'],
dtype='datetime64[ns]', name=('TimeStamp', 'timestamp'), freq='1440T'),
(2, 30): DatetimeIndex(['2018-09-01 02:30:00', '2018-09-02 02:30:00',
'2018-09-03 02:30:00', '2018-09-04 02:30:00',
'2018-09-05 02:30:00', '2018-09-06 02:30:00',
'2018-09-07 02:30:00', '2018-09-08 02:30:00',
'2018-09-09 02:30:00', '2018-09-10 02:30:00',
'2018-09-11 02:30:00', '2018-09-12 02:30:00',
'2018-09-13 02:30:00', '2018-09-14 02:30:00',
'2018-09-15 02:30:00', '2018-09-16 02:30:00',
'2018-09-17 02:30:00', '2018-09-18 02:30:00',
'2018-09-19 02:30:00', '2018-09-20 02:30:00',
'2018-09-21 02:30:00', '2018-09-22 02:30:00',
'2018-09-23 02:30:00', '2018-09-24 02:30:00',
'2018-09-25 02:30:00', '2018-09-26 02:30:00',
'2018-09-27 02:30:00', '2018-09-28 02:30:00',
'2018-09-29 02:30:00', '2018-09-30 02:30:00'],
dtype='datetime64[ns]', name=('TimeStamp', 'timestamp'), freq='1440T'),
(3, 0): DatetimeIndex(['2018-09-01 03:00:00', '2018-09-02 03:00:00',
'2018-09-03 03:00:00', '2018-09-04 03:00:00',
'2018-09-05 03:00:00', '2018-09-06 03:00:00',
'2018-09-07 03:00:00', '2018-09-08 03:00:00',
'2018-09-09 03:00:00', '2018-09-10 03:00:00',
'2018-09-11 03:00:00', '2018-09-12 03:00:00',
'2018-09-13 03:00:00', '2018-09-14 03:00:00',
'2018-09-15 03:00:00', '2018-09-16 03:00:00',
'2018-09-17 03:00:00', '2018-09-18 03:00:00',
'2018-09-19 03:00:00', '2018-09-20 03:00:00',
'2018-09-21 03:00:00', '2018-09-22 03:00:00',
'2018-09-23 03:00:00', '2018-09-24 03:00:00',
'2018-09-25 03:00:00', '2018-09-26 03:00:00',
'2018-09-27 03:00:00', '2018-09-28 03:00:00',
'2018-09-29 03:00:00', '2018-09-30 03:00:00'],
dtype='datetime64[ns]', name=('TimeStamp', 'timestamp'), freq='1440T'),
(3, 30): DatetimeIndex(['2018-09-01 03:30:00', '2018-09-02 03:30:00',
'2018-09-03 03:30:00', '2018-09-04 03:30:00',
'2018-09-05 03:30:00', '2018-09-06 03:30:00',
'2018-09-07 03:30:00', '2018-09-08 03:30:00',
'2018-09-09 03:30:00', '2018-09-10 03:30:00',
'2018-09-11 03:30:00', '2018-09-12 03:30:00',
'2018-09-13 03:30:00', '2018-09-14 03:30:00',
'2018-09-15 03:30:00', '2018-09-16 03:30:00',
'2018-09-17 03:30:00', '2018-09-18 03:30:00',
'2018-09-19 03:30:00', '2018-09-20 03:30:00',
'2018-09-21 03:30:00', '2018-09-22 03:30:00',
'2018-09-23 03:30:00', '2018-09-24 03:30:00',
'2018-09-25 03:30:00', '2018-09-26 03:30:00',
'2018-09-27 03:30:00', '2018-09-28 03:30:00',
'2018-09-29 03:30:00', '2018-09-30 03:30:00'],
dtype='datetime64[ns]', name=('TimeStamp', 'timestamp'), freq='1440T'),
(4, 0): DatetimeIndex(['2018-09-01 04:00:00', '2018-09-02 04:00:00',
'2018-09-03 04:00:00', '2018-09-04 04:00:00',
'2018-09-05 04:00:00', '2018-09-06 04:00:00',
'2018-09-07 04:00:00', '2018-09-08 04:00:00',
'2018-09-09 04:00:00', '2018-09-10 04:00:00',
'2018-09-11 04:00:00', '2018-09-12 04:00:00',
'2018-09-13 04:00:00', '2018-09-14 04:00:00',
'2018-09-15 04:00:00', '2018-09-16 04:00:00',
'2018-09-17 04:00:00', '2018-09-18 04:00:00',
'2018-09-19 04:00:00', '2018-09-20 04:00:00',
'2018-09-21 04:00:00', '2018-09-22 04:00:00',
'2018-09-23 04:00:00', '2018-09-24 04:00:00',
'2018-09-25 04:00:00', '2018-09-26 04:00:00',
'2018-09-27 04:00:00', '2018-09-28 04:00:00',
'2018-09-29 04:00:00', '2018-09-30 04:00:00'],
dtype='datetime64[ns]', name=('TimeStamp', 'timestamp'), freq='1440T'),
(4, 30): DatetimeIndex(['2018-09-01 04:30:00', '2018-09-02 04:30:00',
'2018-09-03 04:30:00', '2018-09-04 04:30:00',
'2018-09-05 04:30:00', '2018-09-06 04:30:00',
'2018-09-07 04:30:00', '2018-09-08 04:30:00',
'2018-09-09 04:30:00', '2018-09-10 04:30:00',
'2018-09-11 04:30:00', '2018-09-12 04:30:00',
'2018-09-13 04:30:00', '2018-09-14 04:30:00',
'2018-09-15 04:30:00', '2018-09-16 04:30:00',
'2018-09-17 04:30:00', '2018-09-18 04:30:00',
'2018-09-19 04:30:00', '2018-09-20 04:30:00',
'2018-09-21 04:30:00', '2018-09-22 04:30:00',
'2018-09-23 04:30:00', '2018-09-24 04:30:00',
'2018-09-25 04:30:00', '2018-09-26 04:30:00',
'2018-09-27 04:30:00', '2018-09-28 04:30:00',
'2018-09-29 04:30:00', '2018-09-30 04:30:00'],
dtype='datetime64[ns]', name=('TimeStamp', 'timestamp'), freq='1440T'),
(5, 0): DatetimeIndex(['2018-09-01 05:00:00', '2018-09-02 05:00:00',
'2018-09-03 05:00:00', '2018-09-04 05:00:00',
'2018-09-05 05:00:00', '2018-09-06 05:00:00',
'2018-09-07 05:00:00', '2018-09-08 05:00:00',
'2018-09-09 05:00:00', '2018-09-10 05:00:00',
'2018-09-11 05:00:00', '2018-09-12 05:00:00',
'2018-09-13 05:00:00', '2018-09-14 05:00:00',
'2018-09-15 05:00:00', '2018-09-16 05:00:00',
'2018-09-17 05:00:00', '2018-09-18 05:00:00',
'2018-09-19 05:00:00', '2018-09-20 05:00:00',
'2018-09-21 05:00:00', '2018-09-22 05:00:00',
'2018-09-23 05:00:00', '2018-09-24 05:00:00',
'2018-09-25 05:00:00', '2018-09-26 05:00:00',
'2018-09-27 05:00:00', '2018-09-28 05:00:00',
'2018-09-29 05:00:00', '2018-09-30 05:00:00'],
dtype='datetime64[ns]', name=('TimeStamp', 'timestamp'), freq='1440T'),
(5, 30): DatetimeIndex(['2018-09-01 05:30:00', '2018-09-02 05:30:00',
'2018-09-03 05:30:00', '2018-09-04 05:30:00',
'2018-09-05 05:30:00', '2018-09-06 05:30:00',
'2018-09-07 05:30:00', '2018-09-08 05:30:00',
'2018-09-09 05:30:00', '2018-09-10 05:30:00',
'2018-09-11 05:30:00', '2018-09-12 05:30:00',
'2018-09-13 05:30:00', '2018-09-14 05:30:00',
'2018-09-15 05:30:00', '2018-09-16 05:30:00',
'2018-09-17 05:30:00', '2018-09-18 05:30:00',
'2018-09-19 05:30:00', '2018-09-20 05:30:00',
'2018-09-21 05:30:00', '2018-09-22 05:30:00',
'2018-09-23 05:30:00', '2018-09-24 05:30:00',
'2018-09-25 05:30:00', '2018-09-26 05:30:00',
'2018-09-27 05:30:00', '2018-09-28 05:30:00',
'2018-09-29 05:30:00', '2018-09-30 05:30:00'],
dtype='datetime64[ns]', name=('TimeStamp', 'timestamp'), freq='1440T'),
(6, 0): DatetimeIndex(['2018-09-01 06:00:00', '2018-09-02 06:00:00',
'2018-09-03 06:00:00', '2018-09-04 06:00:00',
'2018-09-05 06:00:00', '2018-09-06 06:00:00',
'2018-09-07 06:00:00', '2018-09-08 06:00:00',
'2018-09-09 06:00:00', '2018-09-10 06:00:00',
'2018-09-11 06:00:00', '2018-09-12 06:00:00',
'2018-09-13 06:00:00', '2018-09-14 06:00:00',
'2018-09-15 06:00:00', '2018-09-16 06:00:00',
'2018-09-17 06:00:00', '2018-09-18 06:00:00',
'2018-09-19 06:00:00', '2018-09-20 06:00:00',
'2018-09-21 06:00:00', '2018-09-22 06:00:00',
'2018-09-23 06:00:00', '2018-09-24 06:00:00',
'2018-09-25 06:00:00', '2018-09-26 06:00:00',
'2018-09-27 06:00:00', '2018-09-28 06:00:00',
'2018-09-29 06:00:00', '2018-09-30 06:00:00'],
dtype='datetime64[ns]', name=('TimeStamp', 'timestamp'), freq='1440T'),
(6, 30): DatetimeIndex(['2018-09-01 06:30:00', '2018-09-02 06:30:00',
'2018-09-03 06:30:00', '2018-09-04 06:30:00',
'2018-09-05 06:30:00', '2018-09-06 06:30:00',
'2018-09-07 06:30:00', '2018-09-08 06:30:00',
'2018-09-09 06:30:00', '2018-09-10 06:30:00',
'2018-09-11 06:30:00', '2018-09-12 06:30:00',
'2018-09-13 06:30:00', '2018-09-14 06:30:00',
'2018-09-15 06:30:00', '2018-09-16 06:30:00',
'2018-09-17 06:30:00', '2018-09-18 06:30:00',
'2018-09-19 06:30:00', '2018-09-20 06:30:00',
'2018-09-21 06:30:00', '2018-09-22 06:30:00',
'2018-09-23 06:30:00', '2018-09-24 06:30:00',
'2018-09-25 06:30:00', '2018-09-26 06:30:00',
'2018-09-27 06:30:00', '2018-09-28 06:30:00',
'2018-09-29 06:30:00', '2018-09-30 06:30:00'],
dtype='datetime64[ns]', name=('TimeStamp', 'timestamp'), freq='1440T'),
(7, 0): DatetimeIndex(['2018-09-01 07:00:00', '2018-09-02 07:00:00',
'2018-09-03 07:00:00', '2018-09-04 07:00:00',
'2018-09-05 07:00:00', '2018-09-06 07:00:00',
'2018-09-07 07:00:00', '2018-09-08 07:00:00',
'2018-09-09 07:00:00', '2018-09-10 07:00:00',
'2018-09-11 07:00:00', '2018-09-12 07:00:00',
'2018-09-13 07:00:00', '2018-09-14 07:00:00',
'2018-09-15 07:00:00', '2018-09-16 07:00:00',
'2018-09-17 07:00:00', '2018-09-18 07:00:00',
'2018-09-19 07:00:00', '2018-09-20 07:00:00',
'2018-09-21 07:00:00', '2018-09-22 07:00:00',
'2018-09-23 07:00:00', '2018-09-24 07:00:00',
'2018-09-25 07:00:00', '2018-09-26 07:00:00',
'2018-09-27 07:00:00', '2018-09-28 07:00:00',
'2018-09-29 07:00:00', '2018-09-30 07:00:00'],
dtype='datetime64[ns]', name=('TimeStamp', 'timestamp'), freq='1440T'),
(7, 30): DatetimeIndex(['2018-09-01 07:30:00', '2018-09-02 07:30:00',
'2018-09-03 07:30:00', '2018-09-04 07:30:00',
'2018-09-05 07:30:00', '2018-09-06 07:30:00',
'2018-09-07 07:30:00', '2018-09-08 07:30:00',
'2018-09-09 07:30:00', '2018-09-10 07:30:00',
'2018-09-11 07:30:00', '2018-09-12 07:30:00',
'2018-09-13 07:30:00', '2018-09-14 07:30:00',
'2018-09-15 07:30:00', '2018-09-16 07:30:00',
'2018-09-17 07:30:00', '2018-09-18 07:30:00',
'2018-09-19 07:30:00', '2018-09-20 07:30:00',
'2018-09-21 07:30:00', '2018-09-22 07:30:00',
'2018-09-23 07:30:00', '2018-09-24 07:30:00',
'2018-09-25 07:30:00', '2018-09-26 07:30:00',
'2018-09-27 07:30:00', '2018-09-28 07:30:00',
'2018-09-29 07:30:00', '2018-09-30 07:30:00'],
dtype='datetime64[ns]', name=('TimeStamp', 'timestamp'), freq='1440T'),
(8, 0): DatetimeIndex(['2018-09-01 08:00:00', '2018-09-02 08:00:00',
'2018-09-03 08:00:00', '2018-09-04 08:00:00',
'2018-09-05 08:00:00', '2018-09-06 08:00:00',
'2018-09-07 08:00:00', '2018-09-08 08:00:00',
'2018-09-09 08:00:00', '2018-09-10 08:00:00',
'2018-09-11 08:00:00', '2018-09-12 08:00:00',
'2018-09-13 08:00:00', '2018-09-14 08:00:00',
'2018-09-15 08:00:00', '2018-09-16 08:00:00',
'2018-09-17 08:00:00', '2018-09-18 08:00:00',
'2018-09-19 08:00:00', '2018-09-20 08:00:00',
'2018-09-21 08:00:00', '2018-09-22 08:00:00',
'2018-09-23 08:00:00', '2018-09-24 08:00:00',
'2018-09-25 08:00:00', '2018-09-26 08:00:00',
'2018-09-27 08:00:00', '2018-09-28 08:00:00',
'2018-09-29 08:00:00', '2018-09-30 08:00:00'],
dtype='datetime64[ns]', name=('TimeStamp', 'timestamp'), freq='1440T'),
(8, 30): DatetimeIndex(['2018-09-01 08:30:00', '2018-09-02 08:30:00',
'2018-09-03 08:30:00', '2018-09-04 08:30:00',
'2018-09-05 08:30:00', '2018-09-06 08:30:00',
'2018-09-07 08:30:00', '2018-09-08 08:30:00',
'2018-09-09 08:30:00', '2018-09-10 08:30:00',
'2018-09-11 08:30:00', '2018-09-12 08:30:00',
'2018-09-13 08:30:00', '2018-09-14 08:30:00',
'2018-09-15 08:30:00', '2018-09-16 08:30:00',
'2018-09-17 08:30:00', '2018-09-18 08:30:00',
'2018-09-19 08:30:00', '2018-09-20 08:30:00',
'2018-09-21 08:30:00', '2018-09-22 08:30:00',
'2018-09-23 08:30:00', '2018-09-24 08:30:00',
'2018-09-25 08:30:00', '2018-09-26 08:30:00',
'2018-09-27 08:30:00', '2018-09-28 08:30:00',
'2018-09-29 08:30:00', '2018-09-30 08:30:00'],
dtype='datetime64[ns]', name=('TimeStamp', 'timestamp'), freq='1440T'),
(9, 0): DatetimeIndex(['2018-09-01 09:00:00', '2018-09-02 09:00:00',
'2018-09-03 09:00:00', '2018-09-04 09:00:00',
'2018-09-05 09:00:00', '2018-09-06 09:00:00',
'2018-09-07 09:00:00', '2018-09-08 09:00:00',
'2018-09-09 09:00:00', '2018-09-10 09:00:00',
'2018-09-11 09:00:00', '2018-09-12 09:00:00',
'2018-09-13 09:00:00', '2018-09-14 09:00:00',
'2018-09-15 09:00:00', '2018-09-16 09:00:00',
'2018-09-17 09:00:00', '2018-09-18 09:00:00',
'2018-09-19 09:00:00', '2018-09-20 09:00:00',
'2018-09-21 09:00:00', '2018-09-22 09:00:00',
'2018-09-23 09:00:00', '2018-09-24 09:00:00',
'2018-09-25 09:00:00', '2018-09-26 09:00:00',
'2018-09-27 09:00:00', '2018-09-28 09:00:00',
'2018-09-29 09:00:00', '2018-09-30 09:00:00'],
dtype='datetime64[ns]', name=('TimeStamp', 'timestamp'), freq='1440T'),
(9, 30): DatetimeIndex(['2018-09-01 09:30:00', '2018-09-02 09:30:00',
'2018-09-03 09:30:00', '2018-09-04 09:30:00',
'2018-09-05 09:30:00', '2018-09-06 09:30:00',
'2018-09-07 09:30:00', '2018-09-08 09:30:00',
'2018-09-09 09:30:00', '2018-09-10 09:30:00',
'2018-09-11 09:30:00', '2018-09-12 09:30:00',
'2018-09-13 09:30:00', '2018-09-14 09:30:00',
'2018-09-15 09:30:00', '2018-09-16 09:30:00',
'2018-09-17 09:30:00', '2018-09-18 09:30:00',
'2018-09-19 09:30:00', '2018-09-20 09:30:00',
'2018-09-21 09:30:00', '2018-09-22 09:30:00',
'2018-09-23 09:30:00', '2018-09-24 09:30:00',
'2018-09-25 09:30:00', '2018-09-26 09:30:00',
'2018-09-27 09:30:00', '2018-09-28 09:30:00',
'2018-09-29 09:30:00', '2018-09-30 09:30:00'],
dtype='datetime64[ns]', name=('TimeStamp', 'timestamp'), freq='1440T'),
(10, 0): DatetimeIndex(['2018-09-01 10:00:00', '2018-09-02 10:00:00',
'2018-09-03 10:00:00', '2018-09-04 10:00:00',
'2018-09-05 10:00:00', '2018-09-06 10:00:00',
'2018-09-07 10:00:00', '2018-09-08 10:00:00',
'2018-09-09 10:00:00', '2018-09-10 10:00:00',
'2018-09-11 10:00:00', '2018-09-12 10:00:00',
'2018-09-13 10:00:00', '2018-09-14 10:00:00',
'2018-09-15 10:00:00', '2018-09-16 10:00:00',
'2018-09-17 10:00:00', '2018-09-18 10:00:00',
'2018-09-19 10:00:00', '2018-09-20 10:00:00',
'2018-09-21 10:00:00', '2018-09-22 10:00:00',
'2018-09-23 10:00:00', '2018-09-24 10:00:00',
'2018-09-25 10:00:00', '2018-09-26 10:00:00',
'2018-09-27 10:00:00', '2018-09-28 10:00:00',
'2018-09-29 10:00:00', '2018-09-30 10:00:00'],
dtype='datetime64[ns]', name=('TimeStamp', 'timestamp'), freq='1440T'),
(10, 30): DatetimeIndex(['2018-09-01 10:30:00', '2018-09-02 10:30:00',
'2018-09-03 10:30:00', '2018-09-04 10:30:00',
'2018-09-05 10:30:00', '2018-09-06 10:30:00',
'2018-09-07 10:30:00', '2018-09-08 10:30:00',
'2018-09-09 10:30:00', '2018-09-10 10:30:00',
'2018-09-11 10:30:00', '2018-09-12 10:30:00',
'2018-09-13 10:30:00', '2018-09-14 10:30:00',
'2018-09-15 10:30:00', '2018-09-16 10:30:00',
'2018-09-17 10:30:00', '2018-09-18 10:30:00',
'2018-09-19 10:30:00', '2018-09-20 10:30:00',
'2018-09-21 10:30:00', '2018-09-22 10:30:00',
'2018-09-23 10:30:00', '2018-09-24 10:30:00',
'2018-09-25 10:30:00', '2018-09-26 10:30:00',
'2018-09-27 10:30:00', '2018-09-28 10:30:00',
'2018-09-29 10:30:00', '2018-09-30 10:30:00'],
dtype='datetime64[ns]', name=('TimeStamp', 'timestamp'), freq='1440T'),
(11, 0): DatetimeIndex(['2018-09-01 11:00:00', '2018-09-02 11:00:00',
'2018-09-03 11:00:00', '2018-09-04 11:00:00',
'2018-09-05 11:00:00', '2018-09-06 11:00:00',
'2018-09-07 11:00:00', '2018-09-08 11:00:00',
'2018-09-09 11:00:00', '2018-09-10 11:00:00',
'2018-09-11 11:00:00', '2018-09-12 11:00:00',
'2018-09-13 11:00:00', '2018-09-14 11:00:00',
'2018-09-15 11:00:00', '2018-09-16 11:00:00',
'2018-09-17 11:00:00', '2018-09-18 11:00:00',
'2018-09-19 11:00:00', '2018-09-20 11:00:00',
'2018-09-21 11:00:00', '2018-09-22 11:00:00',
'2018-09-23 11:00:00', '2018-09-24 11:00:00',
'2018-09-25 11:00:00', '2018-09-26 11:00:00',
'2018-09-27 11:00:00', '2018-09-28 11:00:00',
'2018-09-29 11:00:00', '2018-09-30 11:00:00'],
dtype='datetime64[ns]', name=('TimeStamp', 'timestamp'), freq='1440T'),
(11, 30): DatetimeIndex(['2018-09-01 11:30:00', '2018-09-02 11:30:00',
'2018-09-03 11:30:00', '2018-09-04 11:30:00',
'2018-09-05 11:30:00', '2018-09-06 11:30:00',
'2018-09-07 11:30:00', '2018-09-08 11:30:00',
'2018-09-09 11:30:00', '2018-09-10 11:30:00',
'2018-09-11 11:30:00', '2018-09-12 11:30:00',
'2018-09-13 11:30:00', '2018-09-14 11:30:00',
'2018-09-15 11:30:00', '2018-09-16 11:30:00',
'2018-09-17 11:30:00', '2018-09-18 11:30:00',
'2018-09-19 11:30:00', '2018-09-20 11:30:00',
'2018-09-21 11:30:00', '2018-09-22 11:30:00',
'2018-09-23 11:30:00', '2018-09-24 11:30:00',
'2018-09-25 11:30:00', '2018-09-26 11:30:00',
'2018-09-27 11:30:00', '2018-09-28 11:30:00',
'2018-09-29 11:30:00', '2018-09-30 11:30:00'],
dtype='datetime64[ns]', name=('TimeStamp', 'timestamp'), freq='1440T'),
(12, 0): DatetimeIndex(['2018-09-01 12:00:00', '2018-09-02 12:00:00',
'2018-09-03 12:00:00', '2018-09-04 12:00:00',
'2018-09-05 12:00:00', '2018-09-06 12:00:00',
'2018-09-07 12:00:00', '2018-09-08 12:00:00',
'2018-09-09 12:00:00', '2018-09-10 12:00:00',
'2018-09-11 12:00:00', '2018-09-12 12:00:00',
'2018-09-13 12:00:00', '2018-09-14 12:00:00',
'2018-09-15 12:00:00', '2018-09-16 12:00:00',
'2018-09-17 12:00:00', '2018-09-18 12:00:00',
'2018-09-19 12:00:00', '2018-09-20 12:00:00',
'2018-09-21 12:00:00', '2018-09-22 12:00:00',
'2018-09-23 12:00:00', '2018-09-24 12:00:00',
'2018-09-25 12:00:00', '2018-09-26 12:00:00',
'2018-09-27 12:00:00', '2018-09-28 12:00:00',
'2018-09-29 12:00:00', '2018-09-30 12:00:00'],
dtype='datetime64[ns]', name=('TimeStamp', 'timestamp'), freq='1440T'),
(12, 30): DatetimeIndex(['2018-09-01 12:30:00', '2018-09-02 12:30:00',
'2018-09-03 12:30:00', '2018-09-04 12:30:00',
'2018-09-05 12:30:00', '2018-09-06 12:30:00',
'2018-09-07 12:30:00', '2018-09-08 12:30:00',
'2018-09-09 12:30:00', '2018-09-10 12:30:00',
'2018-09-11 12:30:00', '2018-09-12 12:30:00',
'2018-09-13 12:30:00', '2018-09-14 12:30:00',
'2018-09-15 12:30:00', '2018-09-16 12:30:00',
'2018-09-17 12:30:00', '2018-09-18 12:30:00',
'2018-09-19 12:30:00', '2018-09-20 12:30:00',
'2018-09-21 12:30:00', '2018-09-22 12:30:00',
'2018-09-23 12:30:00', '2018-09-24 12:30:00',
'2018-09-25 12:30:00', '2018-09-26 12:30:00',
'2018-09-27 12:30:00', '2018-09-28 12:30:00',
'2018-09-29 12:30:00', '2018-09-30 12:30:00'],
dtype='datetime64[ns]', name=('TimeStamp', 'timestamp'), freq='1440T'),
(13, 0): DatetimeIndex(['2018-09-01 13:00:00', '2018-09-02 13:00:00',
'2018-09-03 13:00:00', '2018-09-04 13:00:00',
'2018-09-05 13:00:00', '2018-09-06 13:00:00',
'2018-09-07 13:00:00', '2018-09-08 13:00:00',
'2018-09-09 13:00:00', '2018-09-10 13:00:00',
'2018-09-11 13:00:00', '2018-09-12 13:00:00',
'2018-09-13 13:00:00', '2018-09-14 13:00:00',
'2018-09-15 13:00:00', '2018-09-16 13:00:00',
'2018-09-17 13:00:00', '2018-09-18 13:00:00',
'2018-09-19 13:00:00', '2018-09-20 13:00:00',
'2018-09-21 13:00:00', '2018-09-22 13:00:00',
'2018-09-23 13:00:00', '2018-09-24 13:00:00',
'2018-09-25 13:00:00', '2018-09-26 13:00:00',
'2018-09-27 13:00:00', '2018-09-28 13:00:00',
'2018-09-29 13:00:00', '2018-09-30 13:00:00'],
dtype='datetime64[ns]', name=('TimeStamp', 'timestamp'), freq='1440T'),
(13, 30): DatetimeIndex(['2018-09-01 13:30:00', '2018-09-02 13:30:00',
'2018-09-03 13:30:00', '2018-09-04 13:30:00',
'2018-09-05 13:30:00', '2018-09-06 13:30:00',
'2018-09-07 13:30:00', '2018-09-08 13:30:00',
'2018-09-09 13:30:00', '2018-09-10 13:30:00',
'2018-09-11 13:30:00', '2018-09-12 13:30:00',
'2018-09-13 13:30:00', '2018-09-14 13:30:00',
'2018-09-15 13:30:00', '2018-09-16 13:30:00',
'2018-09-17 13:30:00', '2018-09-18 13:30:00',
'2018-09-19 13:30:00', '2018-09-20 13:30:00',
'2018-09-21 13:30:00', '2018-09-22 13:30:00',
'2018-09-23 13:30:00', '2018-09-24 13:30:00',
'2018-09-25 13:30:00', '2018-09-26 13:30:00',
'2018-09-27 13:30:00', '2018-09-28 13:30:00',
'2018-09-29 13:30:00', '2018-09-30 13:30:00'],
dtype='datetime64[ns]', name=('TimeStamp', 'timestamp'), freq='1440T'),
(14, 0): DatetimeIndex(['2018-09-01 14:00:00', '2018-09-02 14:00:00',
'2018-09-03 14:00:00', '2018-09-04 14:00:00',
'2018-09-05 14:00:00', '2018-09-06 14:00:00',
'2018-09-07 14:00:00', '2018-09-08 14:00:00',
'2018-09-09 14:00:00', '2018-09-10 14:00:00',
'2018-09-11 14:00:00', '2018-09-12 14:00:00',
'2018-09-13 14:00:00', '2018-09-14 14:00:00',
'2018-09-15 14:00:00', '2018-09-16 14:00:00',
'2018-09-17 14:00:00', '2018-09-18 14:00:00',
'2018-09-19 14:00:00', '2018-09-20 14:00:00',
'2018-09-21 14:00:00', '2018-09-22 14:00:00',
'2018-09-23 14:00:00', '2018-09-24 14:00:00',
'2018-09-25 14:00:00', '2018-09-26 14:00:00',
'2018-09-27 14:00:00', '2018-09-28 14:00:00',
'2018-09-29 14:00:00', '2018-09-30 14:00:00'],
dtype='datetime64[ns]', name=('TimeStamp', 'timestamp'), freq='1440T'),
(14, 30): DatetimeIndex(['2018-09-01 14:30:00', '2018-09-02 14:30:00',
'2018-09-03 14:30:00', '2018-09-04 14:30:00',
'2018-09-05 14:30:00', '2018-09-06 14:30:00',
'2018-09-07 14:30:00', '2018-09-08 14:30:00',
'2018-09-09 14:30:00', '2018-09-10 14:30:00',
'2018-09-11 14:30:00', '2018-09-12 14:30:00',
'2018-09-13 14:30:00', '2018-09-14 14:30:00',
'2018-09-15 14:30:00', '2018-09-16 14:30:00',
'2018-09-17 14:30:00', '2018-09-18 14:30:00',
'2018-09-19 14:30:00', '2018-09-20 14:30:00',
'2018-09-21 14:30:00', '2018-09-22 14:30:00',
'2018-09-23 14:30:00', '2018-09-24 14:30:00',
'2018-09-25 14:30:00', '2018-09-26 14:30:00',
'2018-09-27 14:30:00', '2018-09-28 14:30:00',
'2018-09-29 14:30:00', '2018-09-30 14:30:00'],
dtype='datetime64[ns]', name=('TimeStamp', 'timestamp'), freq='1440T'),
(15, 0): DatetimeIndex(['2018-09-01 15:00:00', '2018-09-02 15:00:00',
'2018-09-03 15:00:00', '2018-09-04 15:00:00',
'2018-09-05 15:00:00', '2018-09-06 15:00:00',
'2018-09-07 15:00:00', '2018-09-08 15:00:00',
'2018-09-09 15:00:00', '2018-09-10 15:00:00',
'2018-09-11 15:00:00', '2018-09-12 15:00:00',
'2018-09-13 15:00:00', '2018-09-14 15:00:00',
'2018-09-15 15:00:00', '2018-09-16 15:00:00',
'2018-09-17 15:00:00', '2018-09-18 15:00:00',
'2018-09-19 15:00:00', '2018-09-20 15:00:00',
'2018-09-21 15:00:00', '2018-09-22 15:00:00',
'2018-09-23 15:00:00', '2018-09-24 15:00:00',
'2018-09-25 15:00:00', '2018-09-26 15:00:00',
'2018-09-27 15:00:00', '2018-09-28 15:00:00',
'2018-09-29 15:00:00', '2018-09-30 15:00:00'],
dtype='datetime64[ns]', name=('TimeStamp', 'timestamp'), freq='1440T'),
(15, 30): DatetimeIndex(['2018-09-01 15:30:00', '2018-09-02 15:30:00',
'2018-09-03 15:30:00', '2018-09-04 15:30:00',
'2018-09-05 15:30:00', '2018-09-06 15:30:00',
'2018-09-07 15:30:00', '2018-09-08 15:30:00',
'2018-09-09 15:30:00', '2018-09-10 15:30:00',
'2018-09-11 15:30:00', '2018-09-12 15:30:00',
'2018-09-13 15:30:00', '2018-09-14 15:30:00',
'2018-09-15 15:30:00', '2018-09-16 15:30:00',
'2018-09-17 15:30:00', '2018-09-18 15:30:00',
'2018-09-19 15:30:00', '2018-09-20 15:30:00',
'2018-09-21 15:30:00', '2018-09-22 15:30:00',
'2018-09-23 15:30:00', '2018-09-24 15:30:00',
'2018-09-25 15:30:00', '2018-09-26 15:30:00',
'2018-09-27 15:30:00', '2018-09-28 15:30:00',
'2018-09-29 15:30:00', '2018-09-30 15:30:00'],
dtype='datetime64[ns]', name=('TimeStamp', 'timestamp'), freq='1440T'),
(16, 0): DatetimeIndex(['2018-09-01 16:00:00', '2018-09-02 16:00:00',
'2018-09-03 16:00:00', '2018-09-04 16:00:00',
'2018-09-05 16:00:00', '2018-09-06 16:00:00',
'2018-09-07 16:00:00', '2018-09-08 16:00:00',
'2018-09-09 16:00:00', '2018-09-10 16:00:00',
'2018-09-11 16:00:00', '2018-09-12 16:00:00',
'2018-09-13 16:00:00', '2018-09-14 16:00:00',
'2018-09-15 16:00:00', '2018-09-16 16:00:00',
'2018-09-17 16:00:00', '2018-09-18 16:00:00',
'2018-09-19 16:00:00', '2018-09-20 16:00:00',
'2018-09-21 16:00:00', '2018-09-22 16:00:00',
'2018-09-23 16:00:00', '2018-09-24 16:00:00',
'2018-09-25 16:00:00', '2018-09-26 16:00:00',
'2018-09-27 16:00:00', '2018-09-28 16:00:00',
'2018-09-29 16:00:00', '2018-09-30 16:00:00'],
dtype='datetime64[ns]', name=('TimeStamp', 'timestamp'), freq='1440T'),
(16, 30): DatetimeIndex(['2018-09-01 16:30:00', '2018-09-02 16:30:00',
'2018-09-03 16:30:00', '2018-09-04 16:30:00',
'2018-09-05 16:30:00', '2018-09-06 16:30:00',
'2018-09-07 16:30:00', '2018-09-08 16:30:00',
'2018-09-09 16:30:00', '2018-09-10 16:30:00',
'2018-09-11 16:30:00', '2018-09-12 16:30:00',
'2018-09-13 16:30:00', '2018-09-14 16:30:00',
'2018-09-15 16:30:00', '2018-09-16 16:30:00',
'2018-09-17 16:30:00', '2018-09-18 16:30:00',
'2018-09-19 16:30:00', '2018-09-20 16:30:00',
'2018-09-21 16:30:00', '2018-09-22 16:30:00',
'2018-09-23 16:30:00', '2018-09-24 16:30:00',
'2018-09-25 16:30:00', '2018-09-26 16:30:00',
'2018-09-27 16:30:00', '2018-09-28 16:30:00',
'2018-09-29 16:30:00', '2018-09-30 16:30:00'],
dtype='datetime64[ns]', name=('TimeStamp', 'timestamp'), freq='1440T'),
(17, 0): DatetimeIndex(['2018-09-01 17:00:00', '2018-09-02 17:00:00',
'2018-09-03 17:00:00', '2018-09-04 17:00:00',
'2018-09-05 17:00:00', '2018-09-06 17:00:00',
'2018-09-07 17:00:00', '2018-09-08 17:00:00',
'2018-09-09 17:00:00', '2018-09-10 17:00:00',
'2018-09-11 17:00:00', '2018-09-12 17:00:00',
'2018-09-13 17:00:00', '2018-09-14 17:00:00',
'2018-09-15 17:00:00', '2018-09-16 17:00:00',
'2018-09-17 17:00:00', '2018-09-18 17:00:00',
'2018-09-19 17:00:00', '2018-09-20 17:00:00',
'2018-09-21 17:00:00', '2018-09-22 17:00:00',
'2018-09-23 17:00:00', '2018-09-24 17:00:00',
'2018-09-25 17:00:00', '2018-09-26 17:00:00',
'2018-09-27 17:00:00', '2018-09-28 17:00:00',
'2018-09-29 17:00:00', '2018-09-30 17:00:00'],
dtype='datetime64[ns]', name=('TimeStamp', 'timestamp'), freq='1440T'),
(17, 30): DatetimeIndex(['2018-09-01 17:30:00', '2018-09-02 17:30:00',
'2018-09-03 17:30:00', '2018-09-04 17:30:00',
'2018-09-05 17:30:00', '2018-09-06 17:30:00',
'2018-09-07 17:30:00', '2018-09-08 17:30:00',
'2018-09-09 17:30:00', '2018-09-10 17:30:00',
'2018-09-11 17:30:00', '2018-09-12 17:30:00',
'2018-09-13 17:30:00', '2018-09-14 17:30:00',
'2018-09-15 17:30:00', '2018-09-16 17:30:00',
'2018-09-17 17:30:00', '2018-09-18 17:30:00',
'2018-09-19 17:30:00', '2018-09-20 17:30:00',
'2018-09-21 17:30:00', '2018-09-22 17:30:00',
'2018-09-23 17:30:00', '2018-09-24 17:30:00',
'2018-09-25 17:30:00', '2018-09-26 17:30:00',
'2018-09-27 17:30:00', '2018-09-28 17:30:00',
'2018-09-29 17:30:00', '2018-09-30 17:30:00'],
dtype='datetime64[ns]', name=('TimeStamp', 'timestamp'), freq='1440T'),
(18, 0): DatetimeIndex(['2018-09-01 18:00:00', '2018-09-02 18:00:00',
'2018-09-03 18:00:00', '2018-09-04 18:00:00',
'2018-09-05 18:00:00', '2018-09-06 18:00:00',
'2018-09-07 18:00:00', '2018-09-08 18:00:00',
'2018-09-09 18:00:00', '2018-09-10 18:00:00',
'2018-09-11 18:00:00', '2018-09-12 18:00:00',
'2018-09-13 18:00:00', '2018-09-14 18:00:00',
'2018-09-15 18:00:00', '2018-09-16 18:00:00',
'2018-09-17 18:00:00', '2018-09-18 18:00:00',
'2018-09-19 18:00:00', '2018-09-20 18:00:00',
'2018-09-21 18:00:00', '2018-09-22 18:00:00',
'2018-09-23 18:00:00', '2018-09-24 18:00:00',
'2018-09-25 18:00:00', '2018-09-26 18:00:00',
'2018-09-27 18:00:00', '2018-09-28 18:00:00',
'2018-09-29 18:00:00', '2018-09-30 18:00:00'],
dtype='datetime64[ns]', name=('TimeStamp', 'timestamp'), freq='1440T'),
(18, 30): DatetimeIndex(['2018-09-01 18:30:00', '2018-09-02 18:30:00',
'2018-09-03 18:30:00', '2018-09-04 18:30:00',
'2018-09-05 18:30:00', '2018-09-06 18:30:00',
'2018-09-07 18:30:00', '2018-09-08 18:30:00',
'2018-09-09 18:30:00', '2018-09-10 18:30:00',
'2018-09-11 18:30:00', '2018-09-12 18:30:00',
'2018-09-13 18:30:00', '2018-09-14 18:30:00',
'2018-09-15 18:30:00', '2018-09-16 18:30:00',
'2018-09-17 18:30:00', '2018-09-18 18:30:00',
'2018-09-19 18:30:00', '2018-09-20 18:30:00',
'2018-09-21 18:30:00', '2018-09-22 18:30:00',
'2018-09-23 18:30:00', '2018-09-24 18:30:00',
'2018-09-25 18:30:00', '2018-09-26 18:30:00',
'2018-09-27 18:30:00', '2018-09-28 18:30:00',
'2018-09-29 18:30:00', '2018-09-30 18:30:00'],
dtype='datetime64[ns]', name=('TimeStamp', 'timestamp'), freq='1440T'),
(19, 0): DatetimeIndex(['2018-09-01 19:00:00', '2018-09-02 19:00:00',
'2018-09-03 19:00:00', '2018-09-04 19:00:00',
'2018-09-05 19:00:00', '2018-09-06 19:00:00',
'2018-09-07 19:00:00', '2018-09-08 19:00:00',
'2018-09-09 19:00:00', '2018-09-10 19:00:00',
'2018-09-11 19:00:00', '2018-09-12 19:00:00',
'2018-09-13 19:00:00', '2018-09-14 19:00:00',
'2018-09-15 19:00:00', '2018-09-16 19:00:00',
'2018-09-17 19:00:00', '2018-09-18 19:00:00',
'2018-09-19 19:00:00', '2018-09-20 19:00:00',
'2018-09-21 19:00:00', '2018-09-22 19:00:00',
'2018-09-23 19:00:00', '2018-09-24 19:00:00',
'2018-09-25 19:00:00', '2018-09-26 19:00:00',
'2018-09-27 19:00:00', '2018-09-28 19:00:00',
'2018-09-29 19:00:00', '2018-09-30 19:00:00'],
dtype='datetime64[ns]', name=('TimeStamp', 'timestamp'), freq='1440T'),
(19, 30): DatetimeIndex(['2018-09-01 19:30:00', '2018-09-02 19:30:00',
'2018-09-03 19:30:00', '2018-09-04 19:30:00',
'2018-09-05 19:30:00', '2018-09-06 19:30:00',
'2018-09-07 19:30:00', '2018-09-08 19:30:00',
'2018-09-09 19:30:00', '2018-09-10 19:30:00',
'2018-09-11 19:30:00', '2018-09-12 19:30:00',
'2018-09-13 19:30:00', '2018-09-14 19:30:00',
'2018-09-15 19:30:00', '2018-09-16 19:30:00',
'2018-09-17 19:30:00', '2018-09-18 19:30:00',
'2018-09-19 19:30:00', '2018-09-20 19:30:00',
'2018-09-21 19:30:00', '2018-09-22 19:30:00',
'2018-09-23 19:30:00', '2018-09-24 19:30:00',
'2018-09-25 19:30:00', '2018-09-26 19:30:00',
'2018-09-27 19:30:00', '2018-09-28 19:30:00',
'2018-09-29 19:30:00', '2018-09-30 19:30:00'],
dtype='datetime64[ns]', name=('TimeStamp', 'timestamp'), freq='1440T'),
(20, 0): DatetimeIndex(['2018-09-01 20:00:00', '2018-09-02 20:00:00',
'2018-09-03 20:00:00', '2018-09-04 20:00:00',
'2018-09-05 20:00:00', '2018-09-06 20:00:00',
'2018-09-07 20:00:00', '2018-09-08 20:00:00',
'2018-09-09 20:00:00', '2018-09-10 20:00:00',
'2018-09-11 20:00:00', '2018-09-12 20:00:00',
'2018-09-13 20:00:00', '2018-09-14 20:00:00',
'2018-09-15 20:00:00', '2018-09-16 20:00:00',
'2018-09-17 20:00:00', '2018-09-18 20:00:00',
'2018-09-19 20:00:00', '2018-09-20 20:00:00',
'2018-09-21 20:00:00', '2018-09-22 20:00:00',
'2018-09-23 20:00:00', '2018-09-24 20:00:00',
'2018-09-25 20:00:00', '2018-09-26 20:00:00',
'2018-09-27 20:00:00', '2018-09-28 20:00:00',
'2018-09-29 20:00:00', '2018-09-30 20:00:00'],
dtype='datetime64[ns]', name=('TimeStamp', 'timestamp'), freq='1440T'),
(20, 30): DatetimeIndex(['2018-09-01 20:30:00', '2018-09-02 20:30:00',
'2018-09-03 20:30:00', '2018-09-04 20:30:00',
'2018-09-05 20:30:00', '2018-09-06 20:30:00',
'2018-09-07 20:30:00', '2018-09-08 20:30:00',
'2018-09-09 20:30:00', '2018-09-10 20:30:00',
'2018-09-11 20:30:00', '2018-09-12 20:30:00',
'2018-09-13 20:30:00', '2018-09-14 20:30:00',
'2018-09-15 20:30:00', '2018-09-16 20:30:00',
'2018-09-17 20:30:00', '2018-09-18 20:30:00',
'2018-09-19 20:30:00', '2018-09-20 20:30:00',
'2018-09-21 20:30:00', '2018-09-22 20:30:00',
'2018-09-23 20:30:00', '2018-09-24 20:30:00',
'2018-09-25 20:30:00', '2018-09-26 20:30:00',
'2018-09-27 20:30:00', '2018-09-28 20:30:00',
'2018-09-29 20:30:00', '2018-09-30 20:30:00'],
dtype='datetime64[ns]', name=('TimeStamp', 'timestamp'), freq='1440T'),
(21, 0): DatetimeIndex(['2018-09-01 21:00:00', '2018-09-02 21:00:00',
'2018-09-03 21:00:00', '2018-09-04 21:00:00',
'2018-09-05 21:00:00', '2018-09-06 21:00:00',
'2018-09-07 21:00:00', '2018-09-08 21:00:00',
'2018-09-09 21:00:00', '2018-09-10 21:00:00',
'2018-09-11 21:00:00', '2018-09-12 21:00:00',
'2018-09-13 21:00:00', '2018-09-14 21:00:00',
'2018-09-15 21:00:00', '2018-09-16 21:00:00',
'2018-09-17 21:00:00', '2018-09-18 21:00:00',
'2018-09-19 21:00:00', '2018-09-20 21:00:00',
'2018-09-21 21:00:00', '2018-09-22 21:00:00',
'2018-09-23 21:00:00', '2018-09-24 21:00:00',
'2018-09-25 21:00:00', '2018-09-26 21:00:00',
'2018-09-27 21:00:00', '2018-09-28 21:00:00',
'2018-09-29 21:00:00', '2018-09-30 21:00:00'],
dtype='datetime64[ns]', name=('TimeStamp', 'timestamp'), freq='1440T'),
(21, 30): DatetimeIndex(['2018-09-01 21:30:00', '2018-09-02 21:30:00',
'2018-09-03 21:30:00', '2018-09-04 21:30:00',
'2018-09-05 21:30:00', '2018-09-06 21:30:00',
'2018-09-07 21:30:00', '2018-09-08 21:30:00',
'2018-09-09 21:30:00', '2018-09-10 21:30:00',
'2018-09-11 21:30:00', '2018-09-12 21:30:00',
'2018-09-13 21:30:00', '2018-09-14 21:30:00',
'2018-09-15 21:30:00', '2018-09-16 21:30:00',
'2018-09-17 21:30:00', '2018-09-18 21:30:00',
'2018-09-19 21:30:00', '2018-09-20 21:30:00',
'2018-09-21 21:30:00', '2018-09-22 21:30:00',
'2018-09-23 21:30:00', '2018-09-24 21:30:00',
'2018-09-25 21:30:00', '2018-09-26 21:30:00',
'2018-09-27 21:30:00', '2018-09-28 21:30:00',
'2018-09-29 21:30:00', '2018-09-30 21:30:00'],
dtype='datetime64[ns]', name=('TimeStamp', 'timestamp'), freq='1440T'),
(22, 0): DatetimeIndex(['2018-09-01 22:00:00', '2018-09-02 22:00:00',
'2018-09-03 22:00:00', '2018-09-04 22:00:00',
'2018-09-05 22:00:00', '2018-09-06 22:00:00',
'2018-09-07 22:00:00', '2018-09-08 22:00:00',
'2018-09-09 22:00:00', '2018-09-10 22:00:00',
'2018-09-11 22:00:00', '2018-09-12 22:00:00',
'2018-09-13 22:00:00', '2018-09-14 22:00:00',
'2018-09-15 22:00:00', '2018-09-16 22:00:00',
'2018-09-17 22:00:00', '2018-09-18 22:00:00',
'2018-09-19 22:00:00', '2018-09-20 22:00:00',
'2018-09-21 22:00:00', '2018-09-22 22:00:00',
'2018-09-23 22:00:00', '2018-09-24 22:00:00',
'2018-09-25 22:00:00', '2018-09-26 22:00:00',
'2018-09-27 22:00:00', '2018-09-28 22:00:00',
'2018-09-29 22:00:00', '2018-09-30 22:00:00'],
dtype='datetime64[ns]', name=('TimeStamp', 'timestamp'), freq='1440T'),
(22, 30): DatetimeIndex(['2018-09-01 22:30:00', '2018-09-02 22:30:00',
'2018-09-03 22:30:00', '2018-09-04 22:30:00',
'2018-09-05 22:30:00', '2018-09-06 22:30:00',
'2018-09-07 22:30:00', '2018-09-08 22:30:00',
'2018-09-09 22:30:00', '2018-09-10 22:30:00',
'2018-09-11 22:30:00', '2018-09-12 22:30:00',
'2018-09-13 22:30:00', '2018-09-14 22:30:00',
'2018-09-15 22:30:00', '2018-09-16 22:30:00',
'2018-09-17 22:30:00', '2018-09-18 22:30:00',
'2018-09-19 22:30:00', '2018-09-20 22:30:00',
'2018-09-21 22:30:00', '2018-09-22 22:30:00',
'2018-09-23 22:30:00', '2018-09-24 22:30:00',
'2018-09-25 22:30:00', '2018-09-26 22:30:00',
'2018-09-27 22:30:00', '2018-09-28 22:30:00',
'2018-09-29 22:30:00', '2018-09-30 22:30:00'],
dtype='datetime64[ns]', name=('TimeStamp', 'timestamp'), freq='1440T'),
(23, 0): DatetimeIndex(['2018-09-01 23:00:00', '2018-09-02 23:00:00',
'2018-09-03 23:00:00', '2018-09-04 23:00:00',
'2018-09-05 23:00:00', '2018-09-06 23:00:00',
'2018-09-07 23:00:00', '2018-09-08 23:00:00',
'2018-09-09 23:00:00', '2018-09-10 23:00:00',
'2018-09-11 23:00:00', '2018-09-12 23:00:00',
'2018-09-13 23:00:00', '2018-09-14 23:00:00',
'2018-09-15 23:00:00', '2018-09-16 23:00:00',
'2018-09-17 23:00:00', '2018-09-18 23:00:00',
'2018-09-19 23:00:00', '2018-09-20 23:00:00',
'2018-09-21 23:00:00', '2018-09-22 23:00:00',
'2018-09-23 23:00:00', '2018-09-24 23:00:00',
'2018-09-25 23:00:00', '2018-09-26 23:00:00',
'2018-09-27 23:00:00', '2018-09-28 23:00:00',
'2018-09-29 23:00:00', '2018-09-30 23:00:00'],
dtype='datetime64[ns]', name=('TimeStamp', 'timestamp'), freq='1440T'),
(23, 30): DatetimeIndex(['2018-09-01 23:30:00', '2018-09-02 23:30:00',
'2018-09-03 23:30:00', '2018-09-04 23:30:00',
'2018-09-05 23:30:00', '2018-09-06 23:30:00',
'2018-09-07 23:30:00', '2018-09-08 23:30:00',
'2018-09-09 23:30:00', '2018-09-10 23:30:00',
'2018-09-11 23:30:00', '2018-09-12 23:30:00',
'2018-09-13 23:30:00', '2018-09-14 23:30:00',
'2018-09-15 23:30:00', '2018-09-16 23:30:00',
'2018-09-17 23:30:00', '2018-09-18 23:30:00',
'2018-09-19 23:30:00', '2018-09-20 23:30:00',
'2018-09-21 23:30:00', '2018-09-22 23:30:00',
'2018-09-23 23:30:00', '2018-09-24 23:30:00',
'2018-09-25 23:30:00', '2018-09-26 23:30:00',
'2018-09-27 23:30:00', '2018-09-28 23:30:00',
'2018-09-29 23:30:00', '2018-09-30 23:30:00'],
dtype='datetime64[ns]', name=('TimeStamp', 'timestamp'), freq='1440T')}
[25]:
grp_hr_min=data_ana.groupby([data_ana.index.hour.rename('hour'),data_ana.index.minute.rename('minute')])
grp_hr_min.quantile([.25,.5,.75])
[25]:
| TSoil100 | TSoil10 | TSoil20 | TSoil30 | TSoil50 | TSoil5 | Tsoil | Tconc | Tdew_der | VP_der | ... | Luw | Luw(uc) | Rn | Sb(csd3) | Sdw | Suw | Pmsl | P | Rain | Rain_accum_der | |||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| degC | degC | degC | degC | degC | degC | degC | degC | degC | hPa | ... | W/m^2 | W/m^2 | W/m^2 | W/m^2 | W/m^2 | W/m^2 | hPa | hPa | mm | mm | |||
| hour | minute | ||||||||||||||||||||||
| 0 | 0 | 0.25 | 16.203333 | 13.750833 | 14.415000 | 14.777500 | 15.242500 | 13.977500 | 7.829167 | 9.912500 | 7.284167 | 10.219167 | ... | 342.727500 | -13.627500 | -44.627500 | -4.658333 | -2.756667 | -0.008333 | 1018.250000 | 1010.228333 | 0.0 | 0.000000 |
| 0.50 | 16.620000 | 16.590000 | 16.726667 | 16.915000 | 16.663333 | 16.576667 | 11.020000 | 13.310000 | 9.248333 | 11.678333 | ... | 349.321667 | -13.311667 | -35.965000 | -3.283333 | -1.746667 | 1.040000 | 1022.050000 | 1014.041667 | 0.0 | 0.000000 | ||
| 0.75 | 16.896667 | 17.685833 | 17.789167 | 17.642500 | 16.966667 | 17.575000 | 14.341667 | 15.930000 | 12.159167 | 14.182500 | ... | 376.979167 | -12.440000 | -16.367500 | -3.116667 | -1.385833 | 1.851667 | 1024.536000 | 1016.394167 | 0.0 | 0.100000 | ||
| 30 | 0.25 | 16.267917 | 14.052500 | 14.885833 | 15.364167 | 15.660000 | 14.264583 | 8.153333 | 10.255000 | 7.198750 | 10.161250 | ... | 342.745417 | -13.530000 | -41.023333 | -4.691667 | -2.285833 | 0.267500 | 1018.135417 | 1010.152500 | 0.0 | 0.000000 | |
| 0.50 | 16.627500 | 16.763333 | 16.780833 | 16.965833 | 16.685833 | 16.637500 | 10.879167 | 13.026667 | 9.775000 | 12.104167 | ... | 356.557500 | -13.142500 | -36.063333 | -3.250000 | -1.840833 | 1.070000 | 1021.210000 | 1013.210833 | 0.0 | 0.000000 | ||
| 0.75 | 16.907500 | 17.606250 | 17.760417 | 17.643333 | 16.975000 | 17.512083 | 14.853750 | 15.783750 | 12.562083 | 14.560833 | ... | 378.645417 | -12.342083 | -22.944167 | -3.116667 | -1.378750 | 1.746667 | 1024.443750 | 1016.322917 | 0.0 | 0.000000 | ||
| 1 | 0 | 0.25 | 16.265417 | 14.017500 | 14.851250 | 15.344583 | 15.652500 | 14.208750 | 8.482917 | 10.040833 | 7.270417 | 10.210417 | ... | 341.416667 | -13.621667 | -41.513750 | -4.662500 | -2.329167 | 0.210000 | 1018.140833 | 1010.163333 | 0.0 | 0.000000 |
| 0.50 | 16.627500 | 16.710833 | 16.765000 | 16.914167 | 16.696667 | 16.525000 | 10.580833 | 12.639167 | 9.548333 | 11.920000 | ... | 354.915000 | -13.010000 | -32.285833 | -3.275000 | -1.727500 | 0.885000 | 1021.006667 | 1013.009167 | 0.0 | 0.000000 | ||
| 0.75 | 16.907500 | 17.500417 | 17.716250 | 17.640417 | 16.975000 | 17.476667 | 13.931250 | 14.882500 | 12.078333 | 14.106667 | ... | 375.659167 | -12.341250 | -11.857500 | -3.116667 | -1.381250 | 1.697083 | 1024.414583 | 1016.280417 | 0.0 | 0.000000 | ||
| 30 | 0.25 | 16.265000 | 13.984583 | 14.813333 | 15.324583 | 15.646250 | 14.150417 | 8.072917 | 10.107500 | 7.085417 | 10.082500 | ... | 339.978750 | -13.687500 | -38.483333 | -4.737500 | -2.952500 | 0.188333 | 1018.021250 | 1010.044167 | 0.0 | 0.000000 | |
| 0.50 | 16.625833 | 16.665000 | 16.751667 | 16.869167 | 16.705833 | 16.419167 | 10.192500 | 12.169167 | 9.403333 | 11.804167 | ... | 355.128333 | -13.090833 | -32.211667 | -3.258333 | -1.605000 | 0.805000 | 1020.862500 | 1012.875833 | 0.0 | 0.000000 | ||
| 0.75 | 16.907083 | 17.442917 | 17.680000 | 17.635000 | 16.977500 | 17.452500 | 13.584583 | 14.760000 | 11.855833 | 13.900833 | ... | 373.794167 | -12.205417 | -17.152917 | -3.104167 | -1.205833 | 1.513750 | 1024.363750 | 1016.224167 | 0.0 | 0.000000 | ||
| 2 | 0 | 0.25 | 16.265000 | 13.944583 | 14.776667 | 15.304167 | 15.633333 | 14.089583 | 7.879167 | 9.941667 | 6.990833 | 10.015417 | ... | 338.578750 | -13.557917 | -41.320833 | -4.712500 | -2.701667 | 0.218333 | 1017.807083 | 1009.843750 | 0.0 | 0.000000 |
| 0.50 | 16.620833 | 16.619167 | 16.737500 | 16.850833 | 16.708333 | 16.312500 | 10.161667 | 11.922500 | 9.426667 | 11.823333 | ... | 352.797500 | -13.080833 | -33.703333 | -3.225000 | -1.951667 | 0.938333 | 1020.971667 | 1012.975833 | 0.0 | 0.000000 | ||
| 0.75 | 16.905000 | 17.381667 | 17.634583 | 17.626667 | 16.983750 | 17.349167 | 13.168750 | 14.348750 | 11.722917 | 13.776667 | ... | 369.042083 | -12.417083 | -21.355833 | -3.087500 | -1.264167 | 1.616667 | 1024.258750 | 1016.122917 | 0.0 | 0.000000 | ||
| 30 | 0.25 | 16.262500 | 13.912917 | 14.743750 | 15.284167 | 15.623333 | 13.973333 | 8.472500 | 10.220417 | 6.977083 | 10.005417 | ... | 338.802500 | -13.490833 | -39.216667 | -4.720833 | -2.523750 | 0.230833 | 1017.760833 | 1009.812917 | 0.0 | 0.000000 | |
| 0.50 | 16.620000 | 16.576667 | 16.720833 | 16.824167 | 16.703333 | 16.152500 | 9.715833 | 11.860000 | 9.263333 | 11.690833 | ... | 352.171667 | -12.970000 | -32.739167 | -3.216667 | -1.779167 | 0.951667 | 1020.985000 | 1012.978333 | 0.0 | 0.000000 | ||
| 0.75 | 16.907500 | 17.366250 | 17.565833 | 17.620417 | 16.986667 | 17.336667 | 12.817500 | 14.175000 | 11.720000 | 13.773333 | ... | 368.262083 | -11.929167 | -12.278333 | -3.100000 | -1.244583 | 1.771667 | 1024.400000 | 1016.244167 | 0.0 | 0.000000 | ||
| 3 | 0 | 0.25 | 16.262917 | 13.882917 | 14.706667 | 15.260000 | 15.608333 | 13.858750 | 8.203750 | 9.963333 | 7.051667 | 10.059583 | ... | 337.852083 | -13.540417 | -40.092500 | -4.762500 | -2.728750 | 0.082500 | 1017.668750 | 1009.731250 | 0.0 | 0.000000 |
| 0.50 | 16.619167 | 16.510000 | 16.710000 | 16.800000 | 16.695000 | 15.970833 | 9.658333 | 11.389167 | 8.945000 | 11.442500 | ... | 351.966667 | -12.900000 | -33.474167 | -3.275000 | -1.742500 | 0.840000 | 1021.013333 | 1012.999167 | 0.0 | 0.000000 | ||
| 0.75 | 16.911667 | 17.302917 | 17.472917 | 17.614167 | 16.992917 | 17.211667 | 12.880000 | 14.024167 | 11.710417 | 13.762917 | ... | 368.078333 | -11.949167 | -13.647500 | -3.141667 | -1.175833 | 1.534167 | 1024.489167 | 1016.322917 | 0.0 | 0.000000 | ||
| 30 | 0.25 | 16.265000 | 13.854167 | 14.672500 | 15.236667 | 15.599583 | 13.750417 | 7.466250 | 9.181250 | 6.967917 | 10.003333 | ... | 337.045000 | -13.541250 | -39.738750 | -4.712500 | -2.542917 | 0.158333 | 1017.531667 | 1009.570833 | 0.0 | 0.000000 | |
| 0.50 | 16.610833 | 16.428333 | 16.695000 | 16.776667 | 16.685000 | 15.790833 | 9.693333 | 11.284167 | 8.705833 | 11.259167 | ... | 349.915000 | -12.868333 | -32.610833 | -3.266667 | -1.925000 | 0.749167 | 1021.084167 | 1012.950833 | 0.0 | 0.000000 | ||
| 0.75 | 16.908750 | 17.230000 | 17.390417 | 17.597083 | 16.993750 | 17.130417 | 12.676667 | 13.838750 | 11.550833 | 13.620417 | ... | 367.637917 | -11.930000 | -9.918333 | -3.116667 | -1.067083 | 1.784583 | 1024.549583 | 1016.378750 | 0.0 | 0.000000 | ||
| 4 | 0 | 0.25 | 16.262917 | 13.823750 | 14.638750 | 15.215000 | 15.587917 | 13.630417 | 7.020833 | 8.679583 | 6.733333 | 9.840833 | ... | 332.952917 | -13.505000 | -38.580000 | -4.720833 | -2.543750 | -0.004167 | 1017.439167 | 1009.487083 | 0.0 | 0.000000 |
| 0.50 | 16.610000 | 16.350000 | 16.662500 | 16.745833 | 16.675000 | 15.623333 | 10.015833 | 10.922500 | 8.683333 | 11.241667 | ... | 350.878333 | -12.883333 | -33.360000 | -3.266667 | -1.720833 | 0.770000 | 1020.995000 | 1012.817500 | 0.0 | 0.000000 | ||
| 0.75 | 16.910000 | 17.180417 | 17.312500 | 17.584167 | 16.995000 | 17.018750 | 12.195000 | 13.671667 | 11.531667 | 13.604167 | ... | 366.963333 | -11.867500 | -19.250833 | -3.100000 | -0.953333 | 1.713333 | 1024.542500 | 1016.370000 | 0.0 | 0.000000 | ||
| 30 | 0.25 | 16.258750 | 13.795417 | 14.608750 | 15.189583 | 15.574167 | 13.599167 | 6.819167 | 8.257083 | 6.815417 | 9.895833 | ... | 334.261667 | -13.524167 | -39.825417 | -4.695833 | -2.263750 | -0.195000 | 1017.468333 | 1009.516250 | 0.0 | 0.000000 | |
| 0.50 | 16.605833 | 16.272500 | 16.625000 | 16.738333 | 16.662500 | 15.496667 | 9.970000 | 10.867500 | 8.516667 | 11.117500 | ... | 351.562500 | -12.814167 | -30.935000 | -3.266667 | -1.651667 | 0.923333 | 1020.936667 | 1012.830000 | 0.0 | 0.000000 | ||
| 0.75 | 16.908333 | 17.150000 | 17.280833 | 17.557083 | 16.994583 | 16.867917 | 11.742500 | 13.452917 | 11.528750 | 13.600000 | ... | 365.616250 | -12.037083 | -7.601667 | -3.116667 | -1.056250 | 2.028333 | 1024.580417 | 1016.400417 | 0.0 | 0.000000 | ||
| ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... |
| 19 | 0 | 0.25 | 16.218750 | 14.350833 | 14.537917 | 14.667500 | 15.144583 | 14.873333 | 10.987500 | 13.338750 | 5.862500 | 9.265417 | ... | 360.194167 | -13.560417 | -47.597500 | -4.512500 | -3.258750 | -0.422917 | 1017.630417 | 1009.685417 | 0.0 | 0.000000 |
| 0.50 | 16.559167 | 17.220833 | 16.961667 | 16.810000 | 16.501667 | 17.337500 | 14.897500 | 17.305000 | 9.290833 | 11.713333 | ... | 375.828333 | -13.407500 | -33.670000 | -3.116667 | -2.529167 | 0.605000 | 1020.815833 | 1012.820000 | 0.0 | 0.000000 | ||
| 0.75 | 16.865833 | 18.263333 | 18.024167 | 17.540417 | 16.868750 | 18.801667 | 17.408333 | 19.542083 | 11.589583 | 13.653333 | ... | 390.057500 | -13.105000 | -16.187917 | -3.066667 | -1.808333 | 1.150000 | 1024.169167 | 1016.102500 | 0.0 | 0.466667 | ||
| 30 | 0.25 | 16.215417 | 14.286667 | 14.551667 | 14.669167 | 15.137083 | 14.685417 | 10.087083 | 12.369167 | 6.012500 | 9.361250 | ... | 354.275000 | -13.763750 | -46.365833 | -4.533333 | -3.226667 | -0.094167 | 1017.781250 | 1009.864167 | 0.0 | 0.000000 | |
| 0.50 | 16.562500 | 17.155000 | 16.970000 | 16.846667 | 16.511667 | 17.161667 | 14.579167 | 16.751667 | 9.266667 | 11.692500 | ... | 373.774167 | -13.465833 | -36.598333 | -3.158333 | -2.703333 | 0.763333 | 1021.010833 | 1013.035000 | 0.0 | 0.000000 | ||
| 0.75 | 16.869167 | 18.221667 | 18.028750 | 17.563750 | 16.872917 | 18.695000 | 16.403750 | 18.902083 | 11.761250 | 13.811667 | ... | 385.471250 | -13.092083 | -16.241667 | -3.083333 | -1.677500 | 1.337500 | 1024.247500 | 1016.189583 | 0.0 | 0.600000 | ||
| 20 | 0 | 0.25 | 16.212083 | 14.223333 | 14.550833 | 14.668333 | 15.130000 | 14.567917 | 9.787500 | 11.679583 | 6.370000 | 9.597917 | ... | 352.318750 | -13.664583 | -45.067500 | -4.562500 | -2.735000 | -0.172500 | 1017.718333 | 1009.790417 | 0.0 | 0.000000 |
| 0.50 | 16.566667 | 17.072500 | 16.967500 | 16.876667 | 16.519167 | 17.003333 | 13.876667 | 16.032500 | 9.390833 | 11.794167 | ... | 371.701667 | -13.368333 | -30.376667 | -3.158333 | -2.260000 | 0.685000 | 1021.007500 | 1013.054167 | 0.0 | 0.000000 | ||
| 0.75 | 16.871250 | 18.187083 | 18.025000 | 17.588750 | 16.882917 | 18.519167 | 16.130000 | 18.427083 | 12.190000 | 14.208750 | ... | 381.597917 | -13.034167 | -11.950000 | -3.087500 | -1.521667 | 1.711667 | 1024.302083 | 1016.225833 | 0.0 | 0.600000 | ||
| 30 | 0.25 | 16.207083 | 14.160000 | 14.537917 | 14.660833 | 15.122500 | 14.487917 | 9.258750 | 11.218333 | 6.777500 | 9.872917 | ... | 350.978750 | -13.640000 | -47.912500 | -4.550000 | -3.377500 | 0.146667 | 1017.690000 | 1009.782083 | 0.0 | 0.000000 | |
| 0.50 | 16.569167 | 16.985833 | 16.956667 | 16.905833 | 16.526667 | 16.844167 | 13.310833 | 15.473333 | 9.355833 | 11.762500 | ... | 369.208333 | -13.450000 | -40.895000 | -3.150000 | -2.111667 | 0.838333 | 1020.967500 | 1013.040833 | 0.0 | 0.000000 | ||
| 0.75 | 16.869167 | 18.155833 | 18.008333 | 17.606250 | 16.889583 | 18.420000 | 15.892083 | 17.898750 | 12.061250 | 14.088333 | ... | 382.229167 | -12.947917 | -20.322083 | -3.104167 | -1.491250 | 1.633333 | 1024.375000 | 1016.292917 | 0.0 | 0.600000 | ||
| 21 | 0 | 0.25 | 16.203750 | 14.104583 | 14.514583 | 14.656250 | 15.114167 | 14.412500 | 8.902917 | 11.015000 | 6.944583 | 9.984583 | ... | 348.611250 | -13.789167 | -47.309583 | -4.550000 | -2.944583 | 0.095000 | 1017.869583 | 1009.963333 | 0.0 | 0.000000 |
| 0.50 | 16.573333 | 16.900000 | 16.934167 | 16.915000 | 16.531667 | 16.722500 | 12.922500 | 14.994167 | 9.108333 | 11.570000 | ... | 367.007500 | -13.415000 | -40.457500 | -3.150000 | -2.433333 | 0.936667 | 1021.177500 | 1013.232500 | 0.0 | 0.000000 | ||
| 0.75 | 16.867083 | 18.125833 | 17.984167 | 17.618750 | 16.897917 | 18.345000 | 15.684583 | 17.723333 | 12.183750 | 14.201250 | ... | 382.695417 | -13.016250 | -20.243750 | -3.070833 | -1.546250 | 1.521250 | 1024.411250 | 1016.250417 | 0.0 | 0.600000 | ||
| 30 | 0.25 | 16.197917 | 14.033750 | 14.490000 | 14.644167 | 15.108333 | 14.335833 | 8.690000 | 10.885833 | 7.119583 | 10.105000 | ... | 347.955000 | -13.728750 | -44.223750 | -4.612500 | -2.977917 | 0.268333 | 1017.934583 | 1009.988750 | 0.0 | 0.000000 | |
| 0.50 | 16.578333 | 16.815000 | 16.907500 | 16.912500 | 16.540833 | 16.615000 | 12.765833 | 14.560833 | 9.133333 | 11.589167 | ... | 365.048333 | -13.325000 | -39.369167 | -3.158333 | -2.130000 | 0.777500 | 1021.355000 | 1013.402500 | 0.0 | 0.000000 | ||
| 0.75 | 16.865833 | 18.080000 | 17.950000 | 17.627917 | 16.909167 | 18.267500 | 15.479583 | 17.270833 | 12.266667 | 14.280833 | ... | 381.662500 | -12.761667 | -14.270833 | -3.087500 | -1.506667 | 1.162500 | 1024.383333 | 1016.211667 | 0.0 | 0.600000 | ||
| 22 | 0 | 0.25 | 16.195833 | 13.962083 | 14.454583 | 14.629583 | 15.102083 | 14.238333 | 8.542083 | 10.610000 | 7.154167 | 10.130417 | ... | 343.875417 | -13.678750 | -44.177083 | -4.608333 | -2.767500 | 0.037500 | 1018.185000 | 1010.280417 | 0.0 | 0.000000 |
| 0.50 | 16.575833 | 16.738333 | 16.870000 | 16.907500 | 16.552500 | 16.513333 | 12.756667 | 14.130833 | 9.285000 | 11.709167 | ... | 363.048333 | -13.334167 | -37.298333 | -3.166667 | -2.230833 | 0.660000 | 1021.529167 | 1013.506667 | 0.0 | 0.000000 | ||
| 0.75 | 16.864167 | 18.016250 | 17.912917 | 17.636250 | 16.931250 | 18.173750 | 15.468750 | 16.788333 | 12.286250 | 14.297083 | ... | 381.725417 | -12.805000 | -19.549167 | -3.091667 | -1.575000 | 1.535000 | 1024.375833 | 1016.211250 | 0.0 | 0.866667 | ||
| 30 | 0.25 | 16.190000 | 13.878333 | 14.414167 | 14.610833 | 15.091250 | 14.150417 | 8.186250 | 10.676667 | 7.070417 | 10.069167 | ... | 342.670833 | -13.789583 | -43.435833 | -4.595833 | -2.568750 | 0.054167 | 1018.100000 | 1010.186667 | 0.0 | 0.000000 | |
| 0.50 | 16.578333 | 16.653333 | 16.830000 | 16.896667 | 16.563333 | 16.431667 | 12.428333 | 14.000833 | 9.183333 | 11.627500 | ... | 362.225000 | -13.132500 | -39.990833 | -3.166667 | -2.050000 | 0.791667 | 1021.570000 | 1013.624167 | 0.0 | 0.000000 | ||
| 0.75 | 16.862500 | 17.964167 | 17.873333 | 17.637917 | 16.954583 | 17.982500 | 14.967500 | 16.335000 | 12.243333 | 14.257500 | ... | 379.055833 | -12.714583 | -16.972500 | -3.116667 | -1.516667 | 1.652500 | 1024.432500 | 1016.257083 | 0.0 | 1.000000 | ||
| 23 | 0 | 0.25 | 16.190417 | 13.811250 | 14.376250 | 14.593333 | 15.081250 | 14.065000 | 8.334167 | 10.341250 | 7.143750 | 10.121667 | ... | 342.039167 | -13.722500 | -44.231667 | -4.650000 | -2.502917 | -0.192500 | 1018.019583 | 1010.107917 | 0.0 | 0.000000 |
| 0.50 | 16.580000 | 16.570833 | 16.785833 | 16.881667 | 16.575833 | 16.367500 | 12.029167 | 13.738333 | 9.428333 | 11.820833 | ... | 361.158333 | -13.383333 | -36.176667 | -3.150000 | -1.864167 | 0.596667 | 1021.540833 | 1013.587500 | 0.0 | 0.000000 | ||
| 0.75 | 16.857083 | 17.900000 | 17.830833 | 17.639167 | 16.962917 | 17.826667 | 14.995000 | 16.264583 | 12.205000 | 14.224583 | ... | 379.963750 | -12.612083 | -16.725000 | -3.087500 | -1.474583 | 1.620833 | 1024.187917 | 1016.026250 | 0.0 | 1.200000 | ||
| 30 | 0.25 | 16.183750 | 13.744583 | 14.336667 | 14.584167 | 15.072083 | 13.971667 | 7.897500 | 10.077083 | 7.185833 | 10.152500 | ... | 342.902917 | -13.610833 | -41.025417 | -4.633333 | -2.833750 | -0.150833 | 1018.043333 | 1010.125000 | 0.0 | 0.000000 | |
| 0.50 | 16.580000 | 16.489167 | 16.739167 | 16.860000 | 16.586667 | 16.315833 | 11.660833 | 13.696667 | 9.204167 | 11.645000 | ... | 358.426667 | -13.324167 | -33.520833 | -3.200000 | -1.727500 | 0.603333 | 1021.575000 | 1013.581667 | 0.0 | 0.000000 | ||
| 0.75 | 16.857500 | 17.813333 | 17.809583 | 17.641250 | 16.970417 | 17.734167 | 14.860000 | 16.039167 | 12.132083 | 14.156250 | ... | 377.024583 | -12.581250 | -14.304167 | -3.104167 | -1.268750 | 1.451250 | 1024.072917 | 1015.892500 | 0.0 | 1.200000 |
144 rows × 44 columns
[26]:
grp_hr_min.quantile([.25,.5,.75]).unstack().Rn.plot()
[26]:
<matplotlib.axes._subplots.AxesSubplot at 0x118bcc4a8>
[30]:
df_quartiles=grp_hr_min.quantile([.25,.5,.75]).unstack().swaplevel(1,2,axis=1)
ax_fill=df_quartiles.Rn.reset_index().plot(y=0.5)
[31]:
ax_fill.fill_between(
df_quartiles.reset_index().index,
df_quartiles.Rn.loc[:, 0.25].values.reshape(-1),
df_quartiles.Rn.loc[:, 0.75].values.reshape(-1),
alpha=0.3)
ax_fill.figure
[31]:
[32]:
df_quartiles.columns=df_quartiles.columns.droplevel(-1)
[33]:
df_quartiles.index=pd.date_range('2018 10 01','2018 10 02',freq='30T')[:-1]
[34]:
ax_fill=df_quartiles.Rn.plot(y=0.5)
ax_fill.fill_between(
df_quartiles.index,
df_quartiles.Rn.loc[:, 0.25],
df_quartiles.Rn.loc[:, 0.75],
alpha=0.3)
# ax_fill.figure
[34]:
<matplotlib.collections.PolyCollection at 0x118e7dc50>
[35]:
# ax_fill=
df_quartiles.swaplevel(0,1,axis=1).loc[:,0.5].plot(y=['Rn','Q_H','Q_E','G'])
# ax_fill.fill_between(
# df_quartiles.index,
# df_quartiles.Rn.loc[:, 0.25],
# df_quartiles.Rn.loc[:, 0.75],
# alpha=0.3)
---------------------------------------------------------------------------
KeyError Traceback (most recent call last)
<ipython-input-35-50624d568c76> in <module>()
1 # ax_fill=
----> 2 df_quartiles.swaplevel(0,1,axis=1).loc[:,0.5].plot(y=['Rn','Q_H','Q_E','G'])
3 # ax_fill.fill_between(
4 # df_quartiles.index,
5 # df_quartiles.Rn.loc[:, 0.25],
/usr/local/lib/python3.7/site-packages/pandas/plotting/_core.py in __call__(self, x, y, kind, ax, subplots, sharex, sharey, layout, figsize, use_index, title, grid, legend, style, logx, logy, loglog, xticks, yticks, xlim, ylim, rot, fontsize, colormap, table, yerr, xerr, secondary_y, sort_columns, **kwds)
2939 fontsize=fontsize, colormap=colormap, table=table,
2940 yerr=yerr, xerr=xerr, secondary_y=secondary_y,
-> 2941 sort_columns=sort_columns, **kwds)
2942 __call__.__doc__ = plot_frame.__doc__
2943
/usr/local/lib/python3.7/site-packages/pandas/plotting/_core.py in plot_frame(data, x, y, kind, ax, subplots, sharex, sharey, layout, figsize, use_index, title, grid, legend, style, logx, logy, loglog, xticks, yticks, xlim, ylim, rot, fontsize, colormap, table, yerr, xerr, secondary_y, sort_columns, **kwds)
1975 yerr=yerr, xerr=xerr,
1976 secondary_y=secondary_y, sort_columns=sort_columns,
-> 1977 **kwds)
1978
1979
/usr/local/lib/python3.7/site-packages/pandas/plotting/_core.py in _plot(data, x, y, subplots, ax, kind, **kwds)
1786
1787 # don't overwrite
-> 1788 data = data[y].copy()
1789
1790 if isinstance(data, ABCSeries):
/usr/local/lib/python3.7/site-packages/pandas/core/frame.py in __getitem__(self, key)
2680 if isinstance(key, (Series, np.ndarray, Index, list)):
2681 # either boolean or fancy integer index
-> 2682 return self._getitem_array(key)
2683 elif isinstance(key, DataFrame):
2684 return self._getitem_frame(key)
/usr/local/lib/python3.7/site-packages/pandas/core/frame.py in _getitem_array(self, key)
2724 return self._take(indexer, axis=0)
2725 else:
-> 2726 indexer = self.loc._convert_to_indexer(key, axis=1)
2727 return self._take(indexer, axis=1)
2728
/usr/local/lib/python3.7/site-packages/pandas/core/indexing.py in _convert_to_indexer(self, obj, axis, is_setter)
1325 if mask.any():
1326 raise KeyError('{mask} not in index'
-> 1327 .format(mask=objarr[mask]))
1328
1329 return com._values_from_object(indexer)
KeyError: "['Q_H' 'Q_E'] not in index"
[36]:
data_ana=pd.concat([data_30min,data_EC],axis=1).astype(float)
[37]:
data_ana.loc[:,['Rn','Q_H','Q_E','G']].plot()
[37]:
<matplotlib.axes._subplots.AxesSubplot at 0x118bcc208>
[38]:
grp_hr_min=data_ana.groupby([data_ana.index.hour.rename('hour'),data_ana.index.minute.rename('minute')])
df_quartiles=grp_hr_min.quantile([.25,.5,.75]).unstack().swaplevel(1,2,axis=1)
[39]:
df_quartiles.swaplevel(0,1,axis=1).loc[:,0.5].plot(y=['Rn','Q_H','Q_E','G'])
[39]:
<matplotlib.axes._subplots.AxesSubplot at 0x119486da0>
understand the “notorious” matplotlib-based plotting: http://pbpython.com/effective-matplotlib.html
[40]:
list_var=['Rn','Q_H','Q_E','G']
df_plot=df_quartiles.loc[:,list_var].swaplevel(0,1,axis=1)
df_plot.index=pd.date_range('2018 10 01','2018 10 02',freq='30T')[:-1]
df_plot.columns=df_plot.columns.droplevel(-1)
ax_fill=df_plot.loc[:,0.5].plot()
# ax_fill.fill_between(
# df_quartiles.index,
# df_quartiles.Rn.loc[:, 0.25],
# df_quartiles.Rn.loc[:, 0.75],
# alpha=0.3)
[41]:
df_plot_var = df_plot.swaplevel(0, 1, axis=1)
fig, ax = plt.subplots(1)
for var in list_var:
df_var = df_plot_var.loc[:, var]
y0 = df_var[0.5]
y1, y2 = df_var[0.75], df_var[0.25]
y0.plot(ax=ax, label=var).fill_between(
df_var.index, y1, y2, alpha=0.3)
[42]:
ax.legend(title='variable')
ax.set_xlabel('time')
ax.set_ylabel('heat flux ($W m^{-2}$)')
import matplotlib.dates as mdates
ax.xaxis.set_major_locator(mdates.HourLocator())
# ax.xaxis.set_major_formatter(mdates.DateFormatter('%H:%M'))
# ax.xaxis.set_minor_formatter(mdates.DateFormatter('%H:%M'))
fig
[42]:
[ ]:
df_plot_var = df_plot.swaplevel(0, 1, axis=1)
idx_dt = mdates.date2num(df_plot_var.index)
df_plot_var.index=idx_dt
fig, ax = plt.subplots(1)
for var in list_var:
df_var = df_plot_var.loc[:, var]
y0 = df_var[0.5]
y1, y2 = df_var[0.75], df_var[0.25]
y0.plot(ax=ax, label=var).fill_between(
df_plot_var.index, y1, y2, alpha=0.3)
ax.xaxis.set_major_locator(mdates.HourLocator(interval=3))
ax.xaxis.set_major_formatter(mdates.DateFormatter('%H:%M'))
[ ]:
df_plot_var = df_plot.swaplevel(0, 1, axis=1)
fig, ax = plt.subplots(1)
ax.xaxis.set_minor_formatter(mdates.DateFormatter('%H:%M'))
for var in list_var:
df_var = df_plot_var.loc[:, var]
y0 = df_var[0.5]
y1, y2 = df_var[0.75], df_var[0.25]
y0.plot(ax=ax, label=var).fill_between(
df_var.index, y1, y2, alpha=0.3)
# ax.xaxis.set_major_locator(mdates.HourLocator())
# ax.xaxis.set_major_formatter(mdates.DateFormatter(''))
** `seaborn tutorial <https://seaborn.pydata.org/tutorial.html>`__**