Dataframe pandas plot chart per row

Question

I have a large Pandas dataframe with a lot of columns and I need to plot a chart per row.

For now I have this in my code:

import pandas as pd
import numpy as np
import matplotlib.pyplot as plt

[...]

df = pd.DataFrame() # DataFrame with 13 columns

for index,row in df.iterrows():
    df2 = pd.DataFrame(row)
    plt.set_title(row)
    plt.bar(df2)
    plt.savefig('./plots/chart_' + index)

But the df2 dataframe inside the for loop is empty...

You don't need a loop. There is a cleaner way to do it. See my answer below. — Sergey Bushmanov
– Sergey Bushmanov, Commented Mar 18, 2020 at 11:13

SerAlejo · Accepted Answer · 2020-03-18 10:55:23Z

1

Do you need df2 for other operations? If not you can skip that step and create your chart directly by using the row variable by changing your code to:

for index,row in df.iterrows():
    plt.bar(row.keys(),row.values)
    plt.savefig('./plots/chart_' + index)

answered Mar 18, 2020 at 10:55

SerAlejo

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Sergey Bushmanov · Accepted Answer · 2020-03-18 11:17:55Z

0

An efficient and clean way to plot pandas df per row is to transpose it.

Suppose we happened to have a small df with 13 columns:

df = pd.DataFrame(np.random.randn(10,13))
df.shape
(10, 13)

Plot per column:

df.plot.bar()
plt.legend(df.columns, loc="right");

Plot per row:

df.T.plot.bar()
plt.legend(df.columns, loc="right");

edited Mar 18, 2020 at 11:17

answered Mar 18, 2020 at 11:07

Sergey Bushmanov

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