Edamame
Edamame

Reputation: 25416

pandas histogram: plot histogram for each column as subplot of a big figure

I am using the following code, trying to plot the histogram of every column of a my pandas data frame df_in as subplot of a big figure.

%matplotlib notebook
from itertools import combinations
import matplotlib.pyplot as plt

fig, axes = plt.subplots(len(df_in.columns) // 3, 3, figsize=(12, 48))
for x in df_in.columns:
    df_in.hist(column = x, bins = 100)

fig.tight_layout()

However, the histogram didn't show in the subplot. Any one knows what I missed? Thanks!

Upvotes: 15

Views: 28137

Answers (4)

Ben Saunders
Ben Saunders

Reputation: 1069

Stumbled on this ancient post and figured I'd add a correct answer, the above answers are mostly right but ignore the fact that they need to +1 the flooring function. Somewhat addressed in @burhan 's answer but just cleaned up a bit here:

import seaborn as sns
from matplotlib import pyplot as plt
import math

def plot_univariate_distributions(df, numcols=3, fig_kwargs = dict()):
    numrows = math.ceil(len(df.columns) / numcols)
    fig, axes = plt.subplots(numrows, numcols, **fig_kwargs)
    for col, ax in zip(df.columns, axes.flat):
        sns.histplot(df[col], ax=ax)
        ax.set_title(col, size=10)
    plt.tight_layout()

plot_univariate_distributions(mydf, fig_kwargs={'figsize':[10,5]})

Upvotes: 0

T D
T D

Reputation: 1150

import pandas as pd
import matplotlib.pyplot as plt
%matplotlib inline

fig, axis = plt.subplots(2,3,figsize=(8, 8))
df_in.hist(ax=axis)

The above will plot a 2*3 (total 6 histogram for your dataframe). Adjust the rows and columns as per your arrangement requirements(# of columns)

My TA @Benjamin once told me , dataframe means do not have to use for loop.

Upvotes: 9

Pascal Antoniou
Pascal Antoniou

Reputation: 311

I can't comment burhan's answer because I don't have enough reputation points. The problem with his answer is that axes isn't one-dimensional, it contains axes triads, so it needs to be unrolled:

%matplotlib notebook
from itertools import combinations
import matplotlib.pyplot as plt

fig, axes = plt.subplots(len(df_in.columns)//3, 3, figsize=(12, 48))

i = 0
for triaxis in axes:
    for axis in triaxis:
        df_in.hist(column = df_in.columns[i], bins = 100, ax=axis)
        i = i+1

Upvotes: 14

burhan
burhan

Reputation: 924

You need to specify which axis you are plotting to. This should work:

fig, axes = plt.subplots(len(df_in.columns)//3, 3, figsize=(12, 48))
for col, axis in zip(df_in.columns, axes):
    df_in.hist(column = col, bins = 100, ax=axis)

Upvotes: 3

Related Questions