In this article, we will discuss how to use axis=0 and axis=1 in pandas using Python.
Sometimes we need to do operations only on rows, and sometimes only on columns, in such situations, we specify the axis parameter. In this article, let’s see a few examples to know when and how to use the axis parameter. In pandas axis = 0 refers to horizontal axis or rows and axis = 1 refers to vertical axis or columns.
AXIS =0
When the axis is set to zero while performing a specific action, the action is performed on rows that satisfy the condition.
Dataset Used:
Example: Using axis=0
Python3
# importing packagesimport pandas as pd # importing our datasetdf = pd.read_csv('hiring.csv') # dropping the column named 'experience'df = df.drop([0, 3], axis=0) # 'viewing the dataframedf.head() |
Output:
Example: Using axis=0
Python3
# importing packagesimport pandas as pd # creating a datasetdf = pd.DataFrame([[1, 2, 3], [4, 5, 6], [7, 8, 9], [10, 11, 12]], columns=['a', 'b', 'c']) # viewing the dataFrameprint(df) # finding mean by rowsdf.mean(axis='rows') |
Output:
AXIS=1
When the axis is set to one while performing a specific action, the action is performed on column(s) that satisfy the condition.
Example: Using axis=1
Python3
# importing packagesimport pandas as pd # importing our datasetdf = pd.read_csv('hiring.csv') # dropping the column named 'experience'df = df.drop(['experience'], axis=1) # 'viewing the dataframedf.head() |
Output:
Example: Using axis=1
Python3
# importing packagesimport pandas as pd # creating a datasetdf = pd.DataFrame([[1, 2, 3], [4, 5, 6], [7, 8, 9], [10, 11, 12]], columns=['a', 'b', 'c']) # viewing the dataFrameprint(df) # finding mean by columnsdf.mean(axis='columns') |
Output:
