Merging two pandas dataframes - results in empty df

Question

I am trying to merge two pandas df:

 Final_data
    sp_return  date  dj_return
0    0.000000  1927   0.306237
1    0.394938  1928   0.512283
2   -0.124227  1929  -0.176560
3   -0.235981  1930  -0.292411
4   -0.416280  1931  -0.478050
5   -0.054336  1932  -0.142564
6    0.454805  1933   0.654280
7   -0.073477  1934   0.025883
8    0.372718  1935   0.345200
9    0.260973  1936   0.230361
10  -0.402949  1937  -0.346893

And the following:

    date         president_name party
0   1921      Warren G. Harding     R
1   1922      Warren G. Harding     R
2   1923        Calvin Coolidge     R
3   1924        Calvin Coolidge     R
4   1925        Calvin Coolidge     R
5   1926        Calvin Coolidge     R
6   1927        Calvin Coolidge     R
7   1928        Calvin Coolidge     R
8   1929         Herbert Hoover     R
9   1930         Herbert Hoover     R
10  1931         Herbert Hoover     R
11  1932         Herbert Hoover     R

Using the following code:

final_data1 = presidents.merge(final_data,  on='date')

However, what I get at the end is an empty "final_data1" df. Do you have any suggestions why this might happen?

Please, advise me this issue.

Check the dtype of your dates. (See presidents.info() and final_data.info() for the dtypes). If one says "object" and the other "int", that would explain the problem. (If the values are strings, the dtype is reported as "object".) — unutbu
– unutbu, Commented Feb 12, 2018 at 14:08

zipa · Accepted Answer · 2018-02-12 14:07:41Z

4

Before merging make sure that datatypes are the same. Or add these lines:

presidents['date'] = presidents['date'].astype(int)
final_data['date'] = final_data['date'].astype(int)

answered Feb 12, 2018 at 14:07

zipa

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1 Comment

jezrael Over a year ago

Nice one - you get it ;)

CezarySzulc · Accepted Answer · 2018-02-12 14:07:14Z

0

My code:

df = pd.DataFrame({'Q4':[2906, 1508,738,206,154], 'i':1000})
df2 = pd.DataFrame({'Q4':[2906, 1508,738,206,1], 'j':2000})
df3 = df.merge(df2, on='Q4', how='outer')
df3.head()


      Q4         i       j
0   2906    1000.0  2000.0
1   1508    1000.0  2000.0
2   738     1000.0  2000.0
3   206     1000.0  2000.0
4   154     1000.0  NaN
5   1          NaN  2000.0

answered Feb 12, 2018 at 14:07

CezarySzulc

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