Pandas compare 1 columns values to another dataframe column, find matching rows

Question

I have a database that I am bringing in a SQL table of events and alarms (df1), and I have a txt file of alarm codes and properties (df2) to watch for. Want to use 1 columns values from df2 that each value needs cross checked against an entire column values in df1, and output the entire rows of any that match into another dataframe df3.

df1     A   B   C   D
0     100  20   1   1
1     101  30   1   1
2     102  21   2   3
3     103  15   2   3
4     104  40   2   3

df2     0   1   2   3   4
0      21   2   2   3   3
1      40   0 NaN NaN NaN

Output entire rows from df1 that column B match with any of df2 column 0 values into df3.

df3     A   B   C   D
0     102  21   2   3
1     104  40   2   3

I was able to get single results using:

df1[df1['B'] == df2.iloc[0,0]]

But I need something that will do this on a larger scale.

sacuL · Accepted Answer · 2018-08-16 21:51:18Z

17

Method 1: `merge`

Use merge, on B and 0. Then select only the df1 columns

df1.merge(df2, left_on='B', right_on='0')[df1.columns]

     A   B  C  D
0  102  21  2  3
1  104  40  2  3

Method 2: `loc`

Alternatively use loc to find rows in df1 where B has a match in df2 column 0 using .isin:

df1.loc[df1.B.isin(df2['0'])]

     A   B  C  D
2  102  21  2  3
4  104  40  2  3

answered Aug 16, 2018 at 21:51

sacuL

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Pandas compare 1 columns values to another dataframe column, find matching rows

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Method 1: `merge`

Method 2: `loc`

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Method 1: merge

Method 2: loc

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Method 1: `merge`

Method 2: `loc`