CODEWITHSUNDEEP
pythonpython-3.xpandasdataframe
mlenthusiast
mlenthusiast

Reputation: 1204

Create new column with conditions from other columns with strings

I want to create a function that will create a new column based on certain conditions in two other columns in one pass. Here's a sample dataframe:

col_a    col_b    col_c
abc      abc      jkl
def      def      mno
ghi      pqr      pqr

So the resulting dataframe I would like is:

col_a    col_b    col_c   col_d
abc      abc      jkl     abc
def      def      mno     def
ghi      xyz      pqr     ghipqr

Assuming there are more columns and rows in this dataframe, I would like to create a function that if col_a == col_b, col_d == col_a. If col_a != col_b, then col_d = col_a + col_c. These columns are all strings.

I tried something like this:

list_1 = df['col_a']==df['col_b']

if list_1 is True:
    pass
elif list_1 is False:
    df['col_d'] = df['col_a'] + df['col_c']

But this didn't seem to work, and it added everything, regardless of if the condition was True or False. Any help would be appreciated!

Upvotes: 3

Views: 70

Answers (2)

Allen Qin
Allen Qin

Reputation: 19957

df['col_d'] = np.where(df.col_a==df.col_b, df.col_a, df.col_a+df.col_c)

or

df['col_d'] = df.col_a + np.where(df.col_a.eq(df.col_b), '', df.col_c)

Upvotes: 3

Chris
Chris

Reputation: 29752

IIUC, you can use pandas.Series.where instead:

df["col_d"] = s.where(s.eq(df["col_b"]), s + df["col_c"])
print(df)

Output:

  col_a col_b col_c   col_d
0   abc   abc   jkl     abc
1   def   def   mno     def
2   ghi   pqr   pqr  ghipqr

Upvotes: 2

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