How to merge two dataframes and retain values in multiple rows?

Question

is the merge function the appropriate way to join the Dataframes 1 and 2 to get the Desired Dataframe?

Dataframe 1:

animal	category	Add-Date
wolf	land	24/09/22
eagle	sky	24/09/22
robin	sky	24/09/22
bear	land	24/09/22
cod	water	24/09/22
salmon	water	24/09/22

Dataframe 2:

category	Tier
land	1
sky	2

Desired Dataframe:

animal	category	Add-Date	Tier
wolf	land	24/09/22	1
eagle	sky	24/09/22	2
robin	sky	24/09/22	2
bear	land	24/09/22	1

The Desired Dataframe is Dataframe 1 with irrelevant categories removed and the appropriate Tier brought across with the category.

I was trying merge, join, etc. but unsure of the best approach or if I am making an error.
Any help much appreciated on the code or method to use.

Asked By: Andrew

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Source

Answer 1

df_merged = pd.merge(df1, df2, how = 'left', on = 'category')

out:

   animal category  Add-Date  Tier
0    wolf     land  24/09/22   1.0
1   eagle      sky  24/09/22   2.0
2   robin      sky  24/09/22   2.0
3    bear     land  24/09/22   1.0
4     cod    water  24/09/22   NaN
5  salmon    water  24/09/22   NaN

you can drop NaN values if needed by

df_merged = pd.merge(df1, df2, how = 'left', on = 'category').dropna()

out:

  animal category  Add-Date  Tier
0   wolf     land  24/09/22   1.0
1  eagle      sky  24/09/22   2.0
2  robin      sky  24/09/22   2.0
3   bear     land  24/09/22   1.0

Answered By: NoobVB

Answer 2

You can perfom an inner join by using pandas.merge to grab the Tier column from df2.

out = df1.merge(df2, on='category')

display(out)

Answered By: L'Artiste

How to merge two dataframes and retain values in multiple rows?

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