Using the axis parameter in pandas

This introduction to pandas is derived from Data School's pandas Q&A with my own notes and code.

Using the "axis" parameter in pandas¶

In [1]:

import pandas as pd

In [4]:

url = 'http://bit.ly/drinksbycountry'
drinks = pd.read_csv(url)

In [5]:

drinks.head()

Out[5]:

	country	beer_servings	spirit_servings	wine_servings	total_litres_of_pure_alcohol	continent
0	Afghanistan	0	0	0	0.0	Asia
1	Albania	89	132	54	4.9	Europe
2	Algeria	25	0	14	0.7	Africa
3	Andorra	245	138	312	12.4	Europe
4	Angola	217	57	45	5.9	Africa

In [6]:

# let's remove "continent" column
# axis=1 drops the column
drinks.drop('continent', axis=1).head()

Out[6]:

	country	beer_servings	spirit_servings	wine_servings	total_litres_of_pure_alcohol
0	Afghanistan	0	0	0	0.0
1	Albania	89	132	54	4.9
2	Algeria	25	0	14	0.7
3	Andorra	245	138	312	12.4
4	Angola	217	57	45	5.9

In [7]:

# drops second row
# axis=0 drops the row
drinks.drop(2, axis=0).head()

Out[7]:

	country	beer_servings	spirit_servings	wine_servings	total_litres_of_pure_alcohol	continent
0	Afghanistan	0	0	0	0.0	Asia
1	Albania	89	132	54	4.9	Europe
3	Andorra	245	138	312	12.4	Europe
4	Angola	217	57	45	5.9	Africa
5	Antigua & Barbuda	102	128	45	4.9	North America

In [8]:

# drops multiple rows
drop_rows = [0, 1]
drinks.drop(drop_rows, axis=0).head()

Out[8]:

	country	beer_servings	spirit_servings	wine_servings	total_litres_of_pure_alcohol	continent
2	Algeria	25	0	14	0.7	Africa
3	Andorra	245	138	312	12.4	Europe
4	Angola	217	57	45	5.9	Africa
5	Antigua & Barbuda	102	128	45	4.9	North America
6	Argentina	193	25	221	8.3	South America

In [10]:

# mean of each numeric column
drinks.mean()

# it is the same as the following command as axis=0 is the default
# drinks.mean(axis=0)
# it instructs pandas to move vertically

Out[10]:

beer_servings                   106.160622
spirit_servings                  80.994819
wine_servings                    49.450777
total_litres_of_pure_alcohol      4.717098
dtype: float64

In [12]:

# mean of each row
# drinks.mean(axis='columns)
drinks.mean(axis=1).head()

Out[12]:

0      0.000
1     69.975
2      9.925
3    176.850
4     81.225
dtype: float64

In [14]:

drinks.mean(axis='index').head()
# this is the same as 
# drinks.mean(axis=0).head()

Out[14]:

beer_servings                   106.160622
spirit_servings                  80.994819
wine_servings                    49.450777
total_litres_of_pure_alcohol      4.717098
dtype: float64

Tags: pandas