转换pandas数据框的特定列的特定行 [英] shift particular rows of a particular column of pandas dataframe

问题描述

我有此数据框

并且正在尝试将在前两列中具有NaNs的行向左移动，因此，现在右边的值将填充此列.这是我目前正在尝试做的事情:

And am trying to shift rows which have NaNs in the first two columns to the left, so the values to the right now fill this column. Here is what i am currently trying to do:

(注意:match数据帧是从以下链接下载的: https://www.kaggle .com/hugomathien/soccer )

(Note: the match dataframe was downloaded from this link: https://www.kaggle.com/hugomathien/soccer)

#original dataframe
<class 'pandas.core.frame.DataFrame'>
Int64Index: 21374 entries, 145 to 25978
Data columns (total 47 columns):
id                  21374 non-null int64
country_id          21374 non-null int64
league_id           21374 non-null int64
season              21374 non-null object
stage               21374 non-null int64
date                21374 non-null object
match_api_id        21374 non-null int64
home_team_api_id    21374 non-null int64
away_team_api_id    21374 non-null int64
home_team_goal      21374 non-null int64
away_team_goal      21374 non-null int64
goal                13325 non-null object
shoton              13325 non-null object
shotoff             13325 non-null object
foulcommit          13325 non-null object
card                13325 non-null object
cross               13325 non-null object
corner              13325 non-null object
possession          13325 non-null object
BSA                 11856 non-null float64
Home Team           21374 non-null object
Away Team           21374 non-null object
League              21374 non-null object
Country             21374 non-null object
home_player_1       21374 non-null object
home_player_2       21374 non-null object
home_player_3       21374 non-null object
home_player_4       21374 non-null object
home_player_5       21374 non-null object
home_player_6       21374 non-null object
home_player_7       21374 non-null object
home_player_8       21374 non-null object
home_player_9       21374 non-null object
home_player_10      21374 non-null object
home_player_11      21374 non-null object
away_player_1       21374 non-null object
away_player_2       21374 non-null object
away_player_3       21374 non-null object
away_player_4       21374 non-null object
away_player_5       21374 non-null object
away_player_6       21374 non-null object
away_player_7       21374 non-null object
away_player_8       21374 non-null object
away_player_9       21374 non-null object
away_player_10      21374 non-null object
away_player_11      21374 non-null object
winner              21374 non-null object
dtypes: float64(1), int64(9), object(37)
memory usage: 7.8+ MB

创建数据框

columns = match.columns[match.columns.get_loc('home_player_1'):match.columns.get_loc('away_player_1')+1].values
columns = list(columns)

player_appearences = match.groupby(columns[0]).size().reset_index()
player_appearences.rename(columns = {0:"Count_{}".format(player_appearences.columns[0][len(player_appearences.columns[0])-1])}, inplace = True, errors='raise')
player_appearences
for i in range(1,12):
    player_appearences2 = match.groupby(columns[i]).size().reset_index()
    player_appearences2
    player_appearences2.rename(columns = {0:"Count_{}".format(player_appearences2.columns[0][len(player_appearences2.columns[0])-1])}, inplace = True, errors='raise')
    player_appearences = player_appearences.merge(right = player_appearences2,how="outer",left_on ="{}".format(player_appearences.columns[0]),right_on = "{}".format(player_appearences2.columns[0]))
    player_appearences
    #overwrite nans in first column with names in current [i] player column

#select rows where first two columns give nan values
player_appearences.loc[(player_appearences.loc[:,"home_player_1"].isna()==True) & (player_appearences.loc[:,"Count_1"].isna()==True),["home_player_1","Count_1"]] = player_appearences.loc[(player_appearences.loc[:,"home_player_1"].isna()==True) & (player_appearences.loc[:,"Count_1"].isna()==True),["home_player_2","Count_2"]]

当我然后打印player_appearences时，数据框保持不变.我不确定它是什么也不做，还是正在创建原始数据帧的副本.谁能告诉我为什么如果有这样的方法为什么不行/建议更好的方法?

When I then print player_appearences the dataframe is unchanged. I'm unsure if its either not doing anything, or it is creating a copy of the original dataframe. Can anyone tell me why this isn't working/suggest a better way if there is one?

推荐答案

使用

Use DataFrame.rename, then you only need DataFrame.stack (dropna = True by default) + DataFrame.unstack:

 df = (df.rename(columns = {'home_player_2':'home_player_1',
                           'Count_2':'Count_1'}).stack().unstack()
       .reindex(columns = df.columns[:2]))
print(df)
  home_player_1 Count_1
0         Aaron       1
1          Adam       2
2         Ziggy       3
3        Zoltan       4

或 DataFrame.shift 与 DataFrame.where :

df.where(df.notna(),df.shift(-1,axis = 1)).iloc[:,:2]


  home_player_1  Count_1
0         Aaron      1.0
1          Adam      2.0
2         Ziggy      3.0
3        Zoltan      4.0

详细信息

print(df.where(df.notna(),df.shift(-1,axis = 1)))
  home_player_1  Count_1 home_player_2  Count_2
0         Aaron      1.0           NaN      NaN
1          Adam      2.0           NaN      NaN
2         Ziggy      3.0         Ziggy      3.0
3        Zoltan      4.0        Zoltan      4.0

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