我有一個大數據框。讓我寫一個示例數據框，讓您理解我的問題。A B C car red 15car blue 20car grey 14bike red 6bike blue 8phone red 9phone blue 11phone grey 10假設 C 列顯示價格。我想添加一個名為“D”的列。此列將回答“讀取的汽車是否比所有汽車的平均價格貴？”。以及其他 A 值的相同問題。我的問題基本上就是這樣。我想看到這個：A B C D car red 15 cheapcar blue 20 expensivecar grey 14 cheapbike red 6 cheapbike blue 8 expensivephone red 9 cheapphone blue 11 expensivephone grey 10 cheap我寫了太多方法來完成這個任務。最后我認為這段代碼可以解決我的問題，但事實并非如此。我用 While 循環嘗試了同樣的事情，但我一直收到 Key Error 0。我該怎么辦？這是我試過的代碼：df["D"] = "cheap"A.values = df.A.unique()for b in A.values: for i in range(len(df.loc[data.A== b])): if df.loc[df.A== b, "C"][i] >= df.loc[df.A== b, "C"].mean(): df.loc[df.A== b, "D"][i] = "expensive"
2 回答
冉冉說
TA貢獻1877條經驗 獲得超1個贊
檢查transform，mean然后做np.where
s = df.groupby('A').C.transform('mean')
df['D'] = np.where(df.C>s, 'expensive', 'cheap')
df
Out[158]:
A B C D
0 car red 15 cheap
1 car blue 20 expensive
2 car grey 14 cheap
3 bike red 6 cheap
4 bike blue 8 expensive
5 phone red 9 cheap
6 phone blue 11 expensive
7 phone grey 10 cheap
慕田峪4524236
TA貢獻1875條經驗 獲得超5個贊
df['D']=np.where(df[['A', 'B', 'C']].groupby('A').apply(lambda x: (x['C'].mean()>=x['C'])),'cheap','expensive')
A B C D
0 car red 15 cheap
1 car blue 20 expensive
2 car grey 14 cheap
3 bike red 6 expensive
4 bike blue 8 cheap
5 phone red 9 cheap
6 phone blue 11 expensive
7 phone grey 10 cheap
怎么運行的
np.where(condition, if met answer, not met answer)
#Apply boolean select to get condition. In this statement we seek to return true if mean is greater than price
condition= df[['A', 'B', 'C']].groupby('A').apply(lambda x: (x['C'].mean()>=x['C']))
if met answer= 'cheap'
not me t answer='expensive'
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