# Plot several plots together as subplots

I try to plot several plots with multiple data series as subplots.

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

df1 = pd.DataFrame({
'Date':['2021-01-01', '2021-01-02', '2021-01-03', '2021-01-04', '2021-01-05'],
'index':[0, 1, 2, 3, 4],
'02K W':[3.5, 0.1, 3, 'nan', 0.2],
'03K W':[4.2, 5.2, 2.5, 3.0, 0.6],
'04K W':[1.5, 2.6, 8.2, 4.2, 5.3]})

df2 = pd.DataFrame({
'Date':['2021-01-01', '2021-01-02', '2021-01-03', '2021-01-04', '2021-01-05'],
'index':[0, 1, 2, 3, 4],
'02K W':[3, 'nan', 5, 3, 5.2],
'03K W':[2.1, 2.9, 2.5, 3.9, 6.7],
'04K W':[1.8, 6.2, 5, 2.5, 3.7]})

df1['Date'] = pd.to_datetime(df1['Date'])
df1 = df1.set_index('index')

for col in df1.columns[1:]:
plt.plot(df1['Date'], df1[col])
``````

At the moment, I can only plot the first plot and I am not sure how I need to assign the `for loop` to the y-axis.

``````fig, (ax1, ax2) = plt.subplots(1, 2)
ax1.plot(df1['Date'], y)
ax2.plot(df2['Date'], y)
``````

Thanks a lot for the advise.

### >Solution :

Is this what you are looking for?

``````fig, (ax1, ax2) = plt.subplots(1, 2)
for col in df1.columns[1:]:
ax1.plot(df1['Date'], df1[col])
ax2.plot(df2['Date'], df2[col])
``````