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Pandas DataFrame | itertuples method

Pandas
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DataFrame
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Iterators
schedule Jul 1, 2022
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Pandas DataFrame.itertuples(~) method is used to iterate over the rows of the DataFrame as named tuples.

Parameters

1. index | boolean | optional

  • If True, then the index (row label) is returned as the first element of the tuple.

  • If False, then the index will be omitted from the tuple.

By default, index=True.

2. name | string or None | optional

The name assigned to the returned tuple. By default, name="Pandas".

Return Value

An iterator over the rows of the DataFrame. The rows are represented using named tuples.

Examples

Consider the following DataFrame:

df = pd.DataFrame({"A":["a","b"],"B":["c","d"]})
df
   A  B
0  a  c
1  b  d

To iterate over the rows with the row label:

for row in df.itertuples():      # or index=True to be explicit
   print("row:", row)
row: Pandas(Index=0, A='a', B='c')
row: Pandas(Index=1, A='b', B='d')

Here, we see Pandas because this is the default name assigned to the returned tuple (i.e. name="Pandas").

To iterate over the rows without the row label, set index=False:

for row in df.itertuples(index=False):
   print("row:", row)
row: Pandas(A='a', B='c')
row: Pandas(A='b', B='d')

To set a custom name for the tuple, set the name parameter:

for row in df.itertuples(name="RoboCat"):
   print("row:", row)
row: RoboCat(Index=0, A='a', B='c')
row: RoboCat(Index=1, A='b', B='d')
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Published by Isshin Inada
Edited by 0 others
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