Create column from dictionary key and merging on list similarity pandas python

Question

I have a dictionary like:

{'A':['John','Mark','Jane'],'B':['Mike','Rob','James']}

and a dataframe like:

Name	x	y
John	—	—
Jane	—	—

I would like to add another column, let’s call it ‘Group’, that fills the dictionary key value if Name matches any one of the inner list items. Ideally will end like this:

Name	x	y	Group
John	—	—	A
Rob	—	—	B

Asked By: Benjamin Blackburn

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Source

Answer 1

One solution can be creating inverse dictionary and then use pd.Series.map:

dct = {"A": ["John", "Mark", "Jane"], "B": ["Mike", "Rob", "James"]}

# 1. create inverse dictionary from dct
inv_dct = {v: k for k, l in dct.items() for v in l}    #inv_dct = {'John': 'A', 'Mark': 'A', 'Jane': 'A', 'Mike': 'B', 'Rob': 'B', 'James': 'B'}

# 2. use .map() to create Group column
df["Group"] = df["Name"].map(inv_dct)

# 3. print the dataframe
print(df)

Prints:

   Name    x    y Group
0  John  ---  ---     A
1   Rob  ---  ---     B

Answered By: Andrej Kesely

Create column from dictionary key and merging on list similarity pandas python

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