CODEWITHSUNDEEP
pythonpandas
user3787893
user3787893

Reputation: 13

pandas dataframe: new column depending on other

I have this dataframe where I want to add another column depending on whether change is greater than a certain value, for example 1.03

so that I start with:

index         change
2000-02-18    0.995383
2000-02-22    0.956925
2000-02-23    0.984765
2000-02-24    1.033910
2000-02-25    1.030220
2000-02-28    1.025333

and it outputs:

index         change       label
2000-02-18    0.995383     0
2000-02-22    0.956925     0
2000-02-23    0.984765     0
2000-02-24    1.033910     1
2000-02-25    1.030220     1
2000-02-28    1.025333     0

Upvotes: 0

Views: 62

Answers (1)

DSM
DSM

Reputation: 353359

You can perform a vectorized comparison:

>>> df["label"] = df["change"] > 1.03
>>> df
        index    change  label
0  2000-02-18  0.995383  False
1  2000-02-22  0.956925  False
2  2000-02-23  0.984765  False
3  2000-02-24  1.033910   True
4  2000-02-25  1.030220   True
5  2000-02-28  1.025333  False

or, if you prefer:

>>> df["label"] = (df["change"] > 1.03).astype(int)
>>> df
        index    change  label
0  2000-02-18  0.995383      0
1  2000-02-22  0.956925      0
2  2000-02-23  0.984765      0
3  2000-02-24  1.033910      1
4  2000-02-25  1.030220      1
5  2000-02-28  1.025333      0

(There are lots of other ways to convert from bool to int (+0, *1, etc.) but this is more explicit.)

Upvotes: 1

Related Questions