Adding a column to pandas dataframe using dictionary with indices

Question

This must be trivial but I just can't find it.

For a given pandas dataframe with some indices, say idx1,idx2,idx3 I would like to add a new column efficiently using a dictionary, so something like this:

What is the best way to do it?

have = pd.DataFrame({"idx1":{"c1":1,"c2":2}, \
                     "idx2":{"c1":3,"c2":4}, \
                     "idx3":{"c1":5,"c2":6}}).transpose()
newColumn = {"idx1":"col","idx2":"to","idx3":"add"}
columnName = "myName"

#Wished output:
want = pd.DataFrame({"idx1":{"c1":1,"c2":2,"myName":"col"}, \
                  "idx2":{"c1":3,"c2":4,"myName":"to"}, \
                  "idx3":{"c1":5,"c2":6,"myName":"add"}}).transpose()

How to make good reproducible pandas examples. Was there anything in the User Guide that might help? There is quite a bit there including how to make a Series or add columns to a DataFrame. — wwii
– wwii, Commented Nov 2, 2020 at 15:40

Suraj · Accepted Answer · 2020-11-02 15:52:12Z

1

have[columnName] = pd.Series(newColumn)

Output :

>> have
    c1  c2  myName
idx1    1   2   col
idx2    3   4   to
idx3    5   6   add

answered Nov 2, 2020 at 15:52

Suraj

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