returning multiple columns after comparing dataframes

Question

I have two dataframe as listed below. It was generated using pandas.

df1

                    0

0       reallocations
1                four
2              payoff

df2

word             frequency

whether          1
House            1
Sniderman        1
payoff           6

My goal here is to read df1[0] and check if it exists in df2[word] if it exists then give me an output in the following format.

word             frequency

four             0    
whether          1
House            1
Sniderman        1
reallocations    0
four             0
payoff           6

Here is what I have tried: df1.intersection(df2). I believe I have to assign a column value for that.

I tried solution from Compare pandas dataframes by multiple columns

I am pretty sure there is a small thing that not allowing me to concatenate the desired result.

Any thoughts?

akuiper · Accepted Answer · 2017-10-14 00:30:07Z

0

You need an outer join:

df1.rename(columns={'0': 'word'}).merge(df2, how='outer').fillna(0)
# or df1.rename(columns={0: 'word'}).merge(df2, how='outer').fillna(0) if column names in df1
# is a number

#   word            frequency
#0  reallocations   0.0
#1  four            0.0
#2  payoff          6.0
#3  whether         1.0
#4  House           1.0
#5  Sniderman       1.0

answered Oct 14, 2017 at 0:30

akuiper

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1 Comment

akuiper Over a year ago

Cool. Glad it helps.

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