如果另一列在DataFram中不为null，则用另一列替换该列

Question

我正在使用padnas处理一个数据帧，在这个数据帧中，如果另一个column值不为null，我必须替换一个列。你知道吗

我的数据帧类似于：

v_4        v5             s_5     vt_5     ex_5          pfv           pfv_cat
0-50      StoreSale     Clothes   8-Apr   above 100   FatimaStore       Shoes
0-50      StoreSale     Clothes   8-Apr   0-50        DiscountWorld     Clothes
51-100    CleanShop     Clothes   4-Dec   51-100      BetterUncle       Shoes

所以，我想用pfv替换v_5，其中pfv不是空的，我该如何实现呢？你知道吗

Answer 1

您可以使用pandas和numpy中的apply方法：

df['v_5'] = df.apply(lambda row: row['pfv'] if row['pfv']==np.NaN else row['v_5'], axis=1)

或者没有numpy：

df['v_5'] = df.apply(lambda row: row['pfv'] if pd.isnull(row['pfv']) else row['v_5'], axis=1)

Answer 2

我的解决方法与耶斯雷尔的相同，但还有一步，基于我用空问题写的一篇文章。 我为没有值的pfv又添加了一行。你知道吗

    data = [['0-50','StoreSale','Clothes','8-Apr','above 100','FatimaStore','Shoes'],
    ['0-50','StoreSale','Clothes','8-Apr','0-50','DiscountWorld','Clothes'],
    ['51-100','CleanShop','Clothes','4-Dec','51-100','BetterUncle','Shoes'],
    ['0-50','StoreSale','Clothes','12-Apr','above 100','','Clothes']]

第一步是处理空值df'是数据帧。你知道吗

    df = df.replace('', np.nan)

          v_4         v5      s_5    vt_5       ex_5            pfv  pfv_cat
    0    0-50  StoreSale  Clothes   8-Apr  above 100    FatimaStore    Shoes
    1    0-50  StoreSale  Clothes   8-Apr       0-50  DiscountWorld  Clothes
    2  51-100  CleanShop  Clothes   4-Dec     51-100    BetterUncle    Shoes
    3    0-50  StoreSale  Clothes  12-Apr  above 100            NaN  Clothes

现在让我们更新v5列。 命令说我们将用v5替换pfv，但是如果pfv是NaN，我们将用v5的当前值替换。你知道吗

    df['v5'] = df['pfv'].fillna(df['v5'])


    print(df)

         v_4             v5      s_5    vt_5       ex_5            pfv  pfv_cat
    0    0-50    FatimaStore  Clothes   8-Apr  above 100    FatimaStore    Shoes
    1    0-50  DiscountWorld  Clothes   8-Apr       0-50  DiscountWorld  Clothes
    2  51-100    BetterUncle  Clothes   4-Dec     51-100    BetterUncle    Shoes
    3    0-50      StoreSale  Clothes  12-Apr  above 100            NaN  Clothes

Answer 3

由于缺少的值是字符串null，请使用：

df.loc[df['pfv'].ne('null'), 'v5'] = df["pfv"]
print (df)
      v_4             v5      s_5   vt_5       ex_5            pfv  pfv_cat
0    0-50      StoreSale  Clothes  8-Apr  above 100           null    Shoes
1    0-50  DiscountWorld  Clothes  8-Apr       0-50  DiscountWorld  Clothes
2  51-100    BetterUncle  Clothes  4-Dec     51-100    BetterUncle    Shoes

如果缺少的值是NaN或Nones（不是字符串），请使用^{}：

df['v5'] = df['pfv'].fillna(df['v5'])

print (df)
      v_4             v5      s_5   vt_5       ex_5            pfv  pfv_cat
0    0-50      StoreSale  Clothes  8-Apr  above 100            NaN    Shoes
1    0-50  DiscountWorld  Clothes  8-Apr       0-50  DiscountWorld  Clothes
2  51-100    BetterUncle  Clothes  4-Dec     51-100    BetterUncle    Shoes