CODEWITHSUNDEEP
pythonpython-3.xpandasloops
user7313804
user7313804

Reputation:

Python Pandas make calculation in single cell

I have a TYPE column and a VOLUME column What I'm looking to do if first check if TYPE column == 'var1'

If so I would like to make a calculation in the VOLUME column.

So far I have something like this:

data.loc[data['TYPE'] == 'var1', ['VOLUME']] * 2
data.loc[data['TYPE'] == 'var1', ['VOLUME']] * 4

This seems to set the entire column that meets the condition to the last variable. So I end up with just two values.

Out:

4
4
4
4
8
8
8

Another option:

data['VOLUME'] = data.loc[data['TYPE'] == 'var1', ['VOLUME']] * 2

This works for the first condition but show NaN for the second condition Then when I run:

data['VOLUME'] = data.loc[data['TYPE'] == 'var2', ['VOLUME']] * 4

The whole column show as NaN.

Upvotes: 1

Views: 1222

Answers (3)

cs95
cs95

Reputation: 402553

Consider a simple example which demonstrates what is happening.

df = pd.DataFrame({'A': [1, 2, 3]})
df

   A
0  1
1  2
2  3

Now, only values below 2 in column "A" are to be modified. So, try something like 

df.loc[df.A < 2, 'A'] * 2

0    2
Name: A, dtype: int64

This series only has 1 row at index 0. If you try assigning this back, the implicit assumption is that the other index values are to be reset to NaN.

df.assign(A=df.loc[df.A < 2, 'A'] * 2)

     A
0  2.0
1  NaN
2  NaN

What we want to do is to modify only the rows we're interested in. This is best done with the in-place modification arithmetic operator *=:

df.loc[df.A < 2, 'A'] *= 2

In your case, it is 

data.loc[data['TYPE'] == 'var1', 'VOLUME'] *= 2

Upvotes: 1

Andy Hayden
Andy Hayden

Reputation: 375535

You can use *= with loc:

In [11]: df = pd.DataFrame([[1], [2]], columns=["A"])

In [12]: df
Out[12]:
   A
0  1
1  2

In [13]: df.loc[df.A == 1, "A"] *= 3

In [14]: df
Out[14]:
   A
0  3
1  2

Upvotes: 1

Polkaguy6000
Polkaguy6000

Reputation: 1208

You are really close. The problem is in how you are storing the result. This should work:

 data.loc[data['TYPE'] == 'var1', ['VOLUME']] = data['VOLUME'] * 2

Upvotes: 1

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