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Pandas DataFrame.iterrows()
If you want to loop over the DataFrame for performing some operations on each of the rows then you can use iterrows() function in Pandas.
Pandas use three functions for iterating over the rows of the DataFrame, i.e., iterrows(), iteritems() and itertuples().
Iterate rows with Pandas iterrows:
The iterrows () is responsible for loop through each row of the DataFrame. It returns an iterator that contains index and data of each row as a Series.
We have the next function to see the content of the iterator.
This function returns each index value along with a series that contain the data in each row.
- iterrows() – used for iterating over the rows as (index, series) pairs.
- iteritems() – used for iterating over the (key, value) pairs.
- itertuples() – used for iterating over the rows as namedtuples.
Yields:
- index: Returns the index of the row and a tuple for the MultiIndex.
- data: Returns the data of the row as a Series.
- it: Returns a generator that iterates over the rows of the frame.
Example1
Output
0 name John degree B.Tech score 90 Name: 0, dtype: object 1 name Smith degree B.Com score 40 Name: 1, dtype: object 2 name Alexander degree M.Com score 80 Name: 2, dtype: object 3 name William degree M.Tech score 98 Name: 3, dtype: object
Example2
Output
0 Name Hire Date Salary Leaves Remaining 0 John Idle 03/15/14 50... Name: 0, dtype: object 1 Name Hire Date Salary Leaves Remaining 1 Smith Gilliam 06/01/15 65000... Name: 1, dtype: object 2 Name Hire Date Salary Leaves Remaining 2 Parker Chapman 05/12/14 45000.0 ... Name: 2, dtype: object 3 Name Hire Date Salary Leaves Remaining 3 Jones Palin 11/01/13 700... Name: 3, dtype: object 4 Name Hire Date Salary Leaves Remaining 4 Terry Gilliam 08/12/14 4800... Name: 4, dtype: object 5 Name Hire Date Salary Leaves Remaining 5 Michael Palin 05/23/13 66000... Name: 5, dtype: object
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