In this article, we will discuss how to loop or Iterate overall or certain columns of a DataFrame? There are various methods to achieve this task.
Let’s first create a Dataframe and see that :
Code :
Python3
# import pandas packageimport pandas as pd# List of Tuplesstudents = [('Ankit', 22, 'A'), ('Swapnil', 22, 'B'), ('Priya', 22, 'B'), ('Shivangi', 22, 'B'), ]# Create a DataFrame objectstu_df = pd.DataFrame(students, columns =['Name', 'Age', 'Section'], index =['1', '2', '3', '4'])stu_df |
Output :
Now let’s see different ways of iterate or certain columns of a DataFrame :
Method #1: Using DataFrame.iteritems():
Dataframe class provides a member function iteritems() which gives an iterator that can be utilized to iterate over all the columns of a data frame. For every column in the Dataframe it returns an iterator to the tuple containing the column name and its contents as series.
Code :
Python3
import pandas as pd# List of Tuplesstudents = [('Ankit', 22, 'A'), ('Swapnil', 22, 'B'), ('Priya', 22, 'B'), ('Shivangi', 22, 'B'), ]# Create a DataFrame objectstu_df = pd.DataFrame(students, columns =['Name', 'Age', 'Section'], index =['1', '2', '3', '4'])# gives a tuple of column name and series# for each column in the dataframefor (columnName, columnData) in stu_df.iteritems(): print('Column Name : ', columnName) print('Column Contents : ', columnData.values) |
Output:
Method #2: Using [ ] operator :
We can iterate over column names and select our desired column.
Code :
Python3
import pandas as pd# List of Tuplesstudents = [('Ankit', 22, 'A'), ('Swapnil', 22, 'B'), ('Priya', 22, 'B'), ('Shivangi', 22, 'B'), ]# Create a DataFrame objectstu_df = pd.DataFrame(students, columns =['Name', 'Age', 'Section'], index =['1', '2', '3', '4'])# Iterate over column namesfor column in stu_df: # Select column contents by column # name using [] operator columnSeriesObj = stu_df[column] print('Column Name : ', column) print('Column Contents : ', columnSeriesObj.values) |
Output:
Method #3: Iterate over more than one column :
Assume we need to iterate more than one column. In order to do that we can choose more than one column from dataframe and iterate over them.
Code :
Python3
import pandas as pd# List of Tuplesstudents = [('Ankit', 22, 'A'), ('Swapnil', 22, 'B'), ('Priya', 22, 'B'), ('Shivangi', 22, 'B'), ]# Create a DataFrame objectstu_df = pd.DataFrame(students, columns =['Name', 'Age', 'Section'], index =['1', '2', '3', '4'])# Iterate over two given columns# only from the dataframefor column in stu_df[['Name', 'Section']]: # Select column contents by column # name using [] operator columnSeriesObj = stu_df[column] print('Column Name : ', column) print('Column Contents : ', columnSeriesObj.values) |
Output:
Method #4: Iterating columns in reverse order :
We can iterate over columns in reverse order as well.
Code :
Python3
import pandas as pd# List of Tuplesstudents = [('Ankit', 22, 'A'), ('Swapnil', 22, 'B'), ('Priya', 22, 'B'), ('Shivangi', 22, 'B'), ]# Create a DataFrame objectstu_df = pd.DataFrame(students, columns =['Name', 'Age', 'Section'], index =['1', '2', '3', '4'])# Iterate over the sequence of column names# in reverse orderfor column in reversed(stu_df.columns): # Select column contents by column # name using [] operator columnSeriesObj = stu_df[column] print('Column Name : ', column) print('Column Contents : ', columnSeriesObj.values) |
Output:
Method #5: Using index (iloc) :
To iterate over the columns of a Dataframe by index we can iterate over a range i.e. 0 to Max number of columns than for each index we can select the contents of the column using iloc[].
Code :
Python3
import pandas as pd# List of Tuplesstudents = [('Ankit', 22, 'A'), ('Swapnil', 22, 'B'), ('Priya', 22, 'B'), ('Shivangi', 22, 'B'), ]# Create a DataFrame objectstu_df = pd.DataFrame(students, columns =['Name', 'Age', 'Section'], index =['1', '2', '3', '4'])# Iterate over the index range from# 0 to max number of columns in dataframefor index in range(stu_df.shape[1]): print('Column Number : ', index) # Select column by index position using iloc[] columnSeriesObj = stu_df.iloc[:, index] print('Column Contents : ', columnSeriesObj.values) |
Output:
