[matplotlib]S5_04_Sub_plots

coin_daily_prices.csv

0.14MB

 

 

In [41]:

import matplotlib.pyplot as plt
import pandas as pd
import datetime

 

In [49]:

# data
investment_df = pd.read_csv('coin_daily_prices.csv'); investment_df

 

Out[49]:

	Date	BTC-USD Price	ETH-USD Price	LTC-USD Price
0	2013-04-29 23:59	134.444000	NaN	4.366760
1	2013-04-30 23:59	144.000000	NaN	4.403520
2	2013-05-01 23:59	139.000000	NaN	4.289540
3	2013-05-02 23:59	116.379997	NaN	3.780020
4	2013-05-03 23:59	106.250000	NaN	3.390440
...	...	...	...	...
2986	2021-07-02 23:59	33549.600180	2109.892677	137.299274
2987	2021-07-03 23:59	33854.421360	2150.835025	136.930584
2988	2021-07-04 23:59	34665.564870	2226.550382	140.317998
2989	2021-07-05 23:59	35284.344430	2321.922836	144.849333
2990	2021-07-06 23:59	33723.509660	2197.919385	137.951668

2991 rows × 4 columns

 

In [52]:

investment_df.plot(x = 'Date', title='Cryto Prices', subplots = True, grid =True, figsize = (15,25))

 

Out[52]:

array([<matplotlib.axes._subplots.AxesSubplot object at 0x7f11989f43a0>,
       <matplotlib.axes._subplots.AxesSubplot object at 0x7f119897eac0>,
       <matplotlib.axes._subplots.AxesSubplot object at 0x7f119896dd30>],
      dtype=object)