Histogram Plot using Pandas¶

Date published: 2018-03-04

Category: Data Visualizations

Subcategory: Pandas Plot

Tags: histogram plot

Import Modules¶

In [1]:

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

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

Read in Tips Dataset from URL¶

In [2]:

df_tips = pd.read_csv('https://raw.githubusercontent.com/mwaskom/seaborn-data/master/tips.csv')

df_tips = pd.read_csv('https://raw.githubusercontent.com/mwaskom/seaborn-data/master/tips.csv')

Preview the Data¶

Preview the top 5 rows¶

In [3]:

df_tips.head()

df_tips.head()

Out[3]:

	total_bill	tip	sex	smoker	day	time	size
0	16.99	1.01	Female	No	Sun	Dinner	2
1	10.34	1.66	Male	No	Sun	Dinner	3
2	21.01	3.50	Male	No	Sun	Dinner	3
3	23.68	3.31	Male	No	Sun	Dinner	2
4	24.59	3.61	Female	No	Sun	Dinner	4

View the count of values per colummn and data types¶

In [4]:

df_tips.info()

df_tips.info()

<class 'pandas.core.frame.DataFrame'>
RangeIndex: 244 entries, 0 to 243
Data columns (total 7 columns):
total_bill    244 non-null float64
tip           244 non-null float64
sex           244 non-null object
smoker        244 non-null object
day           244 non-null object
time          244 non-null object
size          244 non-null int64
dtypes: float64(2), int64(1), object(4)
memory usage: 13.4+ KB

Plot a Simple Histogram of Tip Amounts¶

We access the tip column, call the plot method and pass in hist to the kind argument to output a histogram plot.

In [5]:

df_tips['tip'].plot(kind='hist');

df_tips['tip'].plot(kind='hist');

Plot a Simple Histogram of Total Bill Amounts¶

We access the total_bill column, call the plot method and pass in hist to the kind argument to output a histogram plot.

Here is the Pandas hist method documentation page.

In [6]:

df_tips['total_bill'].plot(kind='hist');

df_tips['total_bill'].plot(kind='hist');

Adjust Plot Styles¶

Below, I'll adjust plot styles so it's easier to interpret this plot.

In [9]:

sns.set(font_scale=1.4)
df_tips['total_bill'].plot(kind='hist', figsize=(10, 10));
plt.xlabel("Total Bill Amount ($)", labelpad=14)
plt.ylabel("Frequency", labelpad=14)
plt.title("Distribution of Tip Bill Amounts ($)", y=1.015, fontsize=22);

sns.set(font_scale=1.4) df_tips['total_bill'].plot(kind='hist', figsize=(10, 10)); plt.xlabel("Total Bill Amount ($)", labelpad=14) plt.ylabel("Frequency", labelpad=14) plt.title("Distribution of Tip Bill Amounts ($)", y=1.015, fontsize=22);