Tim.Lucas - 7 months ago 43

Python Question

This should be a really easy one, but I am close to banging my head against the wall because I can figure out how to this. Any help would be greatly appreciated.

I have a pandas DataFrame with a mixed type column (it's actually Decimal, float and string, but let's just assume it's float and string). I am trying to set the value of all the floats which are smaller than zero to 0. What I have tried so far:

`In [1]: import pandas as pd`

In [2]: ex = [-1, 0, 'rabbit', 'carrots', 10, 24, 'dogs']

In [3]: df = pd.DataFrame(data = ex, columns=['Test'], index = range(len(ex)))

In [4]: Mask = df.loc[:,'Test'].apply(type) != str

In [5]: df.loc[Mask,:] < 0

Out[5]: Test

0 True

1 False

4 False

5 False

Ok great so that works, but now I need to pass this into an

`.ix`

`In [6]: df.ix[df.loc[Mask,'Test'] < 0,'Test'] = 0`

Out[6]: [...] IndexingError: Unalignable boolean Series key provided

This is off course completely understandable, but I do not know how to fix this.

I tried

`.index.tolist()`

`df.loc[Mask,'Test'] < 0`

Any help would be greatly appreciated.

Regards,

Tim

Answer

```
mask = df['Test'].map(lambda x: isinstance(x, (int, float)) and x < 0)
df.ix[mask, 'Test'] = 0
```

Source (Stackoverflow)