Python Pandas根据组

Question

我正在尝试复制＆＃34;正确的填充＆＃34;类似于excel的函数，它填充值直到下一个值不为null / nan / empty。这＆＃34;右填＃34;只有当下一行中的值不为空或＆＃34; nan＆＃34;时才能进行练习。此外，必须为每个群体做到这一点。我有以下pandas数据帧数据集。我当前的输入表是＆＃34;有＆＃34;。我的输出表是＆＃34;想要＆＃34;。

我只是python的初学者。所以任何帮助将不胜感激。 对于那些希望通过分组操作进行此操作的人，数据如下： 表＆＃34;有＆＃34;如下所示，分组字段＆＃34; groups＆＃34;：

import pandas as pd
    have = pd.DataFrame({ \
    "groups": pd.Series(["group1","group1","group1","group2","group2","group2"]) \
    ,"0": pd.Series(["abc","1","something here","abc2","1","something here"]) \
    ,"1": pd.Series(["","2","something here","","","something here"]) \
    ,"2": pd.Series(["","3","something here","","3","something here"]) \
    ,"3": pd.Series(["something","1","something here","something","1","something here"]) \
    ,"4": pd.Series(["","2","something here","","2","something here"]) \
    ,"5": pd.Series(["","","something here","","","something here"]) \
    ,"6": pd.Series(["","","something here","","","something here"]) \
    ,"7": pd.Series(["cdf","5","something here","mnop","5","something here"]) \
    ,"8": pd.Series(["","6","something here","","6","something here"]) \
    ,"9": pd.Series(["xyz","1","something here","xyz","1","something here"]) \
    })

表＆＃34;想要＆＃34;使用分组字段＆＃34; groups＆＃34;：

import pandas as pd
    want = pd.DataFrame({ \
    "groups": pd.Series(["group1","group1","group1","group2","group2","group2"]) \
    ,"0": pd.Series(["abc","1","something here","anything","1","something here"]) \
    ,"1": pd.Series(["abc","2","something here"," anything ","2","something here"]) \
    ,"2": pd.Series(["abc","3","something here"," anything ","3","something here"]) \
    ,"3": pd.Series(["something","1","something here","","","something here"]) \
    ,"4": pd.Series(["something ","2","something here","","","something here"]) \
    ,"5": pd.Series(["","","something here","","","something here"]) \
    ,"6": pd.Series(["","","something here","","","something here"]) \
    ,"7": pd.Series(["cdf","5","something here","mnop","5","something here"]) \
    ,"8": pd.Series(["cdf ","6","something here"," mnop ","6","something here"]) \
    ,"9": pd.Series(["xyz","1","something here","xyz","1","something here"]) \
    })

我尝试使用此代码，但我仍然试图熟悉groupby和apply语句：

grouped=have.groupby('groups') 
have.groupby('groups').apply(lambda g: have.loc[g].isnull() )
#cond = have.loc[1].isnull() | have.loc[1].ne('')
want.loc[0, cond] = want.loc[0, cond].str.strip().replace('', None)
want

Answer 1

def fill(df):
    df = df.copy()
    i0, i1 = df.index[0], df.index[1]
    cond = have.loc[i1].isnull() | have.loc[i1].ne('')
    df.loc[i0, cond] = df.loc[i0, cond].str.strip().replace('', None)
    return df


have.groupby('groups', group_keys=False).apply(fill)