如何在 Pandas 中将值从一个数据帧移动到另一个数据帧？

Question

I have a df1 that looks like this:

           Symbol Order  Shares
Date                           
2009-01-14   AAPL   BUY     150
2009-01-21   AAPL  SELL     150
2009-01-21    IBM   BUY     400

And df2 looks like this:

           GOOG AAPL  XOM  IBM Cash
Date                               
2009-01-14  NaN  NaN  NaN  NaN  NaN
2009-01-21  NaN  NaN  NaN  NaN  NaN

I want to move the values in the first DF to the second so that the amount of shares populates under the appropriate stock symbol. So the above would look like:

           GOOG AAPL  XOM  IBM Cash
Date                               
2009-01-14  NaN  150  NaN  NaN  NaN
2009-01-21  NaN  -150 NaN  400  NaN

How would I move all values that I have in my first dataframe to the second dataframe?

Answer 1

You really don't need df2 here. You can compute the result directly from df using some simple reshaping functions set_index , unstack and reindex . You just need the symbols list.

(df.assign(Shares=np.where(df.Order == 'BUY', df.Shares, -df.Shares))
   .drop('Order', 1)
   .set_index('Symbol', append=True)['Shares']
   .unstack(1)
   .reindex(df2.columns, axis=1))  # you can replace df2.columns with a list 

            GOOG   AAPL  XOM    IBM  Cash
Date                                     
2009-01-14   NaN  150.0  NaN    NaN   NaN
2009-01-21   NaN -150.0  NaN  400.0   NaN

Answer 2

Use np.select to convert numbers to negative if Order == 'SELL' then update

df['Shares'] = np.select([df['Order'] == 'SELL'], [-df['Shares']], df['Shares'])
df2.update(df.pivot(None, 'Symbol', 'Shares'))


            GOOG   AAPL  XOM    IBM  Cash
Date                                     
2009-01-14   NaN  150.0  NaN    NaN   NaN
2009-01-21   NaN -150.0  NaN  400.0   NaN