pandas.DataFrame.iterrows

来源：互联网发布：淘宝视频要求编辑：程序博客网时间：2024/05/21 15:06

iterrows

DataFrame.iterrows()[source]

Iterate over DataFrame rows as (index, Series) pairs. 迭代(iterate)覆盖整个DataFrame的行中，返回(index, Series)对

>>> 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

pandas怎样对数据进行遍历

import numpy as npimport pandas as pddef _map(data, exp):                      for index, row in data.iterrows():   # 获取每行的index、row        for col_name in data.columns:            row[col_name] = exp(row[col_name]) # 把结果返回给data    return datadef _1map(data, exp):    _data = [[exp(row[col_name])               # 把结果转换成2级list             for col_name in data.columns]             for index, row in data.iterrows()            ]    return _dataif __name__ == "__main__":    inp = [{'c1':10, 'c2':100}, {'c1':11,'c2':110}, {'c1':12,'c2':120}]    df = pd.DataFrame(inp)    temp = _map(df, lambda ele: ele+1 )    print temp    _temp = _1map(df, lambda ele: ele+1)    res_data = pd.DataFrame(_temp)         # 对2级list转换成DataFrame    print res_data

参考文献

pandas怎样对数据进行遍历

3 0