熊猫 - 有条件地存储输出

Question

I have a df.apply which return a series with Key/Value like below (let's call it column A):

         Col. A
40237    1.871111
40239    1.280556
40240    1.784167
40241    0.049167
40243    0.011389
40244    0.660278
40245    1.512500

I would like to save these values into various columns using the value of a separate column (column B).

Column B can contain 6 different distinct strings (4 in the example).

         Col. B
40237    Open
40239    Open
40240    In Progress
40241    Closed
40243    Waiting
40244    In Progress
40245    Waiting

I want to save my column A values into one of 4 columns based on value of column B.

End result is:

         Col. A      Col. B        Open Time   In Progress Time  Closed Time Waiting Time
40237    1.871111    Open          1.871111    np.nan            np.nan      np.nan
40239    1.280556    Open          1.280556    np.nan            np.nan      np.nan
40240    1.784167    In Progress   np.nan      1.784167          np.nan      np.nan
40241    0.049167    Closed        np.nan      np.nan            0.049167    np.nan
40243    0.011389    Waiting       np.nan      np.nan            np.nan      0.011389
40244    0.660278    In Progress   np.nan      0.660278          np.nan      np.nan
40245    1.512500    Waiting       np.nan      np.nan            np.nan      1.512500

Now my best efforts to get this to work was:

for key in output.index:
    df.loc[key,(df['Col. B'] + " Time")] = output.loc[key]

However my error is ValueError: cannot index with vector containing NA / NaN values . I'm not sure why exactly, though my columns in general do have plenty of nan's.

Answer 1

Use join of pivot ed DataFrame with add_suffix :

df = df.join(pd.pivot(df.index, df['Col. B'], df['Col. A']).add_suffix(' Time'))

Another solution is pivot by set_index with unstack :

df = df.join(df.set_index('Col. B', append=True)['Col. A'].unstack().add_suffix(' Time'))

print (df)
         Col. A       Col. B  Closed Time  In Progress Time  Open Time  \
40237  1.871111         Open          NaN               NaN   1.871111   
40239  1.280556         Open          NaN               NaN   1.280556   
40240  1.784167  In Progress          NaN          1.784167        NaN   
40241  0.049167       Closed     0.049167               NaN        NaN   
40243  0.011389      Waiting          NaN               NaN        NaN   
40244  0.660278  In Progress          NaN          0.660278        NaN   
40245  1.512500      Waiting          NaN               NaN        NaN   

       Waiting Time  
40237           NaN  
40239           NaN  
40240           NaN  
40241           NaN  
40243      0.011389  
40244           NaN  
40245      1.512500