CODEWITHSUNDEEP
pythonpandas
FLab
FLab

Reputation: 7466

pandas assign with new column name as string

I recently discovered pandas "assign" method which I find very elegant. My issue is that the name of the new column is assigned as keyword, so it cannot have spaces or dashes in it.

df = DataFrame({'A': range(1, 11), 'B': np.random.randn(10)})
df.assign(ln_A=lambda x: np.log(x.A))
        A         B      ln_A
0   1  0.426905  0.000000
1   2 -0.780949  0.693147
2   3 -0.418711  1.098612
3   4 -0.269708  1.386294
4   5 -0.274002  1.609438
5   6 -0.500792  1.791759
6   7  1.649697  1.945910
7   8 -1.495604  2.079442
8   9  0.549296  2.197225
9  10 -0.758542  2.302585

but what if I want to name the new column "ln(A)" for example? E.g.

df.assign(ln(A) = lambda x: np.log(x.A))
df.assign("ln(A)" = lambda x: np.log(x.A))


File "<ipython-input-7-de0da86dce68>", line 1
df.assign(ln(A) = lambda x: np.log(x.A))
SyntaxError: keyword can't be an expression

I know I could rename the column right after the .assign call, but I want to understand more about this method and its syntax.

Upvotes: 76

Views: 44156

Answers (3)

mortysporty
mortysporty

Reputation: 2889

As a lazy workaround you can also use rename

(df
 .assign(temp = lambda x: np.log(x.A))
 .rename({"temp": "ln(A)"}, axis=1))

and if you want to get rid of the "temp" column you could add

(df
 .assign(temp = lambda x: np.log(x.A))
 .rename({"temp": "ln(A)"}, axis=1)
 .drop("temp", axis=1))

Upvotes: 0

Piotr
Piotr

Reputation: 2117

You can pass the keyword arguments to assign as a dictionary, like so:

kwargs = {"ln(A)" : lambda x: np.log(x.A)}
df.assign(**kwargs)

    A         B     ln(A)
0   1  0.500033  0.000000
1   2 -0.392229  0.693147
2   3  0.385512  1.098612
3   4 -0.029816  1.386294
4   5 -2.386748  1.609438
5   6 -1.828487  1.791759
6   7  0.096117  1.945910
7   8 -2.867469  2.079442
8   9 -0.731787  2.197225
9  10 -0.686110  2.302585

Upvotes: 139

piRSquared
piRSquared

Reputation: 294218

assign expects a bunch of key word arguments. It will, in turn, assign columns with the names of the key words. That's handy, but you can't pass an expression as the key word. This is spelled out by @EdChum in the comments with this link

use insert instead for inplace transformation

df.insert(2, 'ln(A)', np.log(df.A))
df

enter image description here

use concat if you don't want inplace

pd.concat([df, np.log(df.A).rename('log(A)')], axis=1)

enter image description here

Upvotes: 9

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