Append column to a dataframe using list comprehension format

Question

I would like to append a column of zeros to a dataframe if the column in question is not already inside the dataframe.

If the dataframe looks like this:

df = pd.DataFrame({'a':[0,1,0], 'c':[1,1,1]})

----------------------------------------------
    a   c
0   0   1
1   1   1
2   0   1

And the complete list of column names that the dataframe should have are:

col_names = ['a', 'b', 'c']

I would like the output to look like this after applying the list comprehension to the df:

    a    b    c
0   0    0    1
1   1    0    1
2   0    0    1

This is the complete code I have so far:

col_names = ['a','b','c']

df = pd.DataFrame({'a':[0,1,0], 'c':[1,1,1]})

# This is what I would like to convert into a list comprehension (one line) format if possible
for col in col_names:
    if col not in df.columns:
        df[col] = 0

# Re-order the columns into the correct order        
df = df[col_names]

print(df)

Asked By: ScottC

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Source

Answer 1

A list comprehension would produce a list. You don’t want a list, you want to add columns to your dataframe. List comprehensions should not be used for side effects, ever.

You can however, produce the columns you want to add as a list and use advanced indexing to assign all the columns at the same time:

df[[col for col in col_names if col not in df.columns]] = 0

Answered By: ddejohn

Append column to a dataframe using list comprehension format

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