How to plot charts side by side with a forloop

Question

i have the following code:

import pandas as pd
from pandas import datetime
from pandas import DataFrame as df
import matplotlib
from pandas_datareader import data as web
import matplotlib.pyplot as plt
import datetime
import numpy as np

stocks = 'GE','F' #<-- In this case there are just 2 symbols but this could be more 
start = datetime.date(2000,1,1)
end = datetime.date.today()

data = web.DataReader(stock, 'yahoo',start, end)

for stock in stocks:
    data.plot(y='Close')
plt.subplot(1,1,2) #<-- Trouble here

Here is my question. How can i plot all the symbols side by side inside the forloop?

Answer 1

You can take the code above and specify figsize parameter.

fig, ax = plt.subplots(1, len(stocks), figsize=(20, 10))

If you want all of your plots on the same row, just modify the first parameter of figsize which is the length of the horizontal axis of the box that contains the subplots.

For example, if you want every plot to be 10x10 :

fig, ax = plt.subplots(1, len(stocks), figsize=(len(stocks)*10, 10))

Answer 2

Here i have used the plot function of dataframe, Also i like plotting in different colors so i do this small trick.

#CODE
import pandas as pd
from pandas import datetime
from pandas import DataFrame as df
import matplotlib
from pandas_datareader import data as web
import matplotlib.pyplot as plt
import datetime
import numpy as np

colors = ["b",'g','r','c','m','y','k']

stocks = 'GE','F' #<-- In this case there are just 2 symbols but this could be more 
start = datetime.date(2000,1,1)
end = datetime.date.today()

data = web.DataReader(stocks, 'yahoo',start, end)

# THIS MAKES A GRID OF 1 ROW and len(stocks) COLUMN and figure size as (width, height) in inches.
fig, axs = plt.subplots(1, len(stocks), figsize=(30, 5))
i = 0

#iterate for each stock
for stock in stocks:
    # i'th close stock will plot on i'th axs (Note: Whatever be your grid)
    data["Close"][stock].plot(ax=axs[i],color=colors[i%len(colors)])
    i += 1

#show plot
plt.show()