CODEWITHSUNDEEP
pythonpandas
Kevin Fang
Kevin Fang

Reputation: 2012

pandas how to outer join without creating new columns

I have 2 pandas dataframes like this:

date      value
20100101  100
20100102  150

date      value
20100102  150.01
20100103  180

The expected output should be:

date      value
20100101  100
20100102  150
20100103  180

The 2nd dataframe always contains newest value that I'd like to add into the 1st dataframe. However, the value on the same day may differ slightly between the two dataframes. I would like to ignore the same dates and focus on adding the new date and value into the 1st dataframe.

I've tried outer join in pandas, but it gives me two columns value_x and value_y because the value are not essentially the same on same dates. Any solution to this?

Upvotes: 1

Views: 438

Answers (1)

jezrael
jezrael

Reputation: 862581

I believe need concat with drop_duplicates:

df = pd.concat([df1,df2]).drop_duplicates('date', keep='last')
print (df)
       date   value
0  20100101  100.00
0  20100102  150.01
1  20100103  180.00

df = pd.concat([df1,df2]).drop_duplicates('date', keep='first')
print (df)
       date  value
0  20100101  100.0
1  20100102  150.0
1  20100103  180.0

Upvotes: 3

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