我正在嘗試根據(jù)條件從 dataframe1 到 dataframe2 提取行，但我很掙扎，有人可以幫助我嗎？那就太棒了。數(shù)據(jù)框1：df1 = pd.DataFrame([[1001, 'democrat',0.23],[1001, 'republican',0.7],[1001, 'others',0.07],[1003, 'democrat',0.33],[1003, 'republican',0.44],[1003, 'others',0.23]], columns=['Fips_code', 'Partisan', 'Vote_Pct'])數(shù)據(jù)框2：df2 = pd.DataFrame([[1001],[1003], [1005]], columns=['Fips_code'])我想根據(jù) fips 代碼條件將三列添加到 dataframe2 中，如下所示 ('democrat_vote_pct','republican_vote_pct','others_vote_pct')。期望出：df2 = pd.DataFrame([[1001,0.23,0.7,0.07],[1003,0.33,0.44,0.23], [1005, NA, NA, NA]], columns=['Fips_code','democrat_vote_pct','republican_vote_pct','others_vote_pct'])請(qǐng)幫我..
1 回答
HUX布斯
TA貢獻(xiàn)1876條經(jīng)驗(yàn) 獲得超6個(gè)贊
你可以嘗試這樣的事情：
_df2 = df1.pivot_table(values='Vote_Pct', index='Fips_code', columns='Partisan')
進(jìn)而：
result = df2.merge(_df2, on='Fips_code', how='left')
這給了你你想要的：
Fips_code democrat others republican
0 1001 0.23 0.07 0.70
1 1003 0.33 0.23 0.44
2 1005 NaN NaN NaN
如果您希望列具有不同的名稱，只需給它一個(gè).rename()
new_cols = {'democrat': 'democrat_pct_votes',
'others': 'others_pct_votes',
'republican': 'republican_pct_votes'}
df2.rename(new_cols, axis=1, inplace=True)
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