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I have dataframe total_year, which contains three columns (year, action, comedy) .
total_year
I want to plot the year column on the x-axis, and action & comedy both on the y-axis.
How can I plot two columns (action and comedy) on y-axis?
My code plots only one column on y-axis.
total_year[-15:].plot(x='year', y='action', figsize=(10,5), grid=True)
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Pandas has a tight integration with Matplotlib. You can plot data directly from your DataFrame using the plot() method. To plot multiple data columns in single frame we simply have to pass the list of columns to the y argument of the plot function.
To plot a specific column, use the selection method of the subset data tutorial in combination with the plot() method. Hence, the plot() method works on both Series and DataFrame .
Matplotlib bar chart multiple columns We use the plot() method to draw a bar chart and to define multiple columns, we use the DataFrame object. Example: Here we are going to create multiple bar charts by using the DataFrame object of Pandas.
Several column names may be provided to the y argument of the pandas plotting function. Those should be specified in a list, as follows.
df.plot(x="year", y=["action", "comedy"])
Complete example:
import matplotlib.pyplot as plt
import pandas as pd
df = pd.DataFrame({"year": [1914,1915,1916,1919,1920],
"action" : [2.6,3.4,3.25,2.8,1.75],
"comedy" : [2.5,2.9,3.0,3.3,3.4] })
df.plot(x="year", y=["action", "comedy"])
plt.show()
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Pandas.DataFrame.plot() per default uses index for plotting X axis, all other numeric columns will be used as Y values.
So setting year column as index will do the trick:
total_year.set_index('year').plot(figsize=(10,5), grid=True)
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