Pandas dataframe merge with update data

Question

I hawe two DataFrame:

df1 = pd.DataFrame({'date':['2017-01-01','2017-01-02','2017-01-03','2017-01-04','2017-01-05'], 'value':[1,1,1,1,1]})
df2 = pd.DataFrame({'date':['2017-01-04','2017-01-05','2017-01-06','2017-01-07','2017-01-08'], 'value':[2,2,2,2,2]})

date        value      date        value         
2017-01-01      1      2017-01-04      2
2017-01-02      1      2017-01-05      2
2017-01-03      1      2017-01-06      2
2017-01-04      1      2017-01-07      2
2017-01-05      1      2017-01-08      2

Need to merge df1 and df2 to obtain the following results:

date        value
2017-01-01      1
2017-01-02      1
2017-01-03      1
2017-01-04      2
2017-01-05      2
2017-01-06      2
2017-01-07      2
2017-01-08      2

jezrael · Accepted Answer · 2017-02-09 14:05:12Z

5

You can use concat with drop_duplicates by column date and keep last values:

print (pd.concat([df1, df2]).drop_duplicates('date', keep='last'))
         date  value
0  2017-01-01      1
1  2017-01-02      1
2  2017-01-03      1
0  2017-01-04      2
1  2017-01-05      2
2  2017-01-06      2
3  2017-01-07      2
4  2017-01-08      2

answered Feb 9, 2017 at 14:05

jezrael

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Comments

JP1 · Accepted Answer · 2017-02-09 14:07:21Z

0

I believe you can use the combine_first command built into pandas.

http://pandas.pydata.org/pandas-docs/stable/generated/pandas.DataFrame.combine_first.html

in this case you would do

df3 = df1.combine_first(df2)

Im not certain if it works in the case you are replacing an integer with an integer or if you need to have NaN values in place.

answered Feb 9, 2017 at 14:07

JP1

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