pandas.DataFrame.iterrows#

DataFrame.iterrows()[source]#

Iterate over DataFrame rows as (index, Series) pairs.

Yields:

indexlabel or tuple of label

The index of the row. A tuple for aMultiIndex.

dataSeries

The data of the row as a Series.

See also

DataFrame.itertuples

Iterate over DataFrame rows as namedtuples of the values.

DataFrame.items

Iterate over (column name, Series) pairs.

Notes

1. Becauseiterrows returns a Series for each row,it doesnot preserve dtypes across the rows (dtypes arepreserved across columns for DataFrames).

   To preserve dtypes while iterating over the rows, it is betterto useitertuples() which returns namedtuples of the valuesand which is generally faster thaniterrows.

2. You shouldnever modify something you are iterating over.This is not guaranteed to work in all cases. Depending on thedata types, the iterator returns a copy and not a view, and writingto it will have no effect.

Examples

>>>df=pd.DataFrame([[1,1.5]],columns=['int','float'])>>>row=next(df.iterrows())[1]>>>rowint      1.0float    1.5Name: 0, dtype: float64>>>print(row['int'].dtype)float64>>>print(df['int'].dtype)int64