How to plot multiple pandas columns
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()
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)
- When using
pandas.DataFrame.plot
, it's only necessary to specify a column to thex
parameter.- The caveat is, the rest of the columns with
numeric
values will be used fory
. - The following code contains extra columns to demonstrate. Note,
'date'
is left as astring
. However, if'date'
is converted to adatetime
dtype
, the plot API will also plot the'date'
column on the y-axis.
- The caveat is, the rest of the columns with
- If the dataframe includes many columns, some of which should not be plotted, then specify the
y
parameter as shown in this answer, but if the dataframe contains only columns to be plotted, then specify only thex
parameter. - In cases where the index is to be used as the x-axis, then it is not necessary to specify
x=
.
import pandas as pd
# test data
data = {'year': [1914, 1915, 1916, 1919, 1920],
'action': [2.67, 3.43, 3.26, 2.82, 1.75],
'comedy': [2.53, 2.93, 3.02, 3.37, 3.45],
'test1': ['a', 'b', 'c', 'd', 'e'],
'date': ['1914-01-01', '1915-01-01', '1916-01-01', '1919-01-01', '1920-01-01']}
# create the dataframe
df = pd.DataFrame(data)
# display(df)
year action comedy test1 date
0 1914 2.67 2.53 a 1914-01-01
1 1915 3.43 2.93 b 1915-01-01
2 1916 3.26 3.02 c 1916-01-01
3 1919 2.82 3.37 d 1919-01-01
4 1920 1.75 3.45 e 1920-01-01
# plot the dataframe
df.plot(x='year', figsize=(10, 5), grid=True)