CODEWITHSUNDEEP
python-3.xpandas
PyAnton
PyAnton

Reputation: 53

Pandas: Update values of a column

I have a large dataframe with multiple columns (sample shown below). I want to update the values of one particular (population column) column by dividing the values of it by 1000.

City     Population
Paris    23456
Lisbon   123466
Madrid   1254
Pekin    86648

I have tried df['Population'].apply(lambda x: int(str(x))/1000)

and 

df['Population'].apply(lambda x: int(x)/1000)

Both give me the error

ValueError: invalid literal for int() with base 10: '...'

Upvotes: 5

Views: 25264

Answers (1)

fuglede
fuglede

Reputation: 18221

If your DataFrame really does look as presented, then the second example should work just fine (with the int not even being necessary):

In [16]: df
Out[16]: 
     City  Population
0   Paris       23456
1  Lisbon      123466
2  Madrid        1254
3   Pekin       86648

In [17]: df['Population'].apply(lambda x: x/1000)
Out[17]: 
0     23.456
1    123.466
2      1.254
3     86.648
Name: Population, dtype: float64

In [18]: df['Population']/1000
Out[18]: 
0     23.456
1    123.466
2      1.254
3     86.648

However, from the error, it seems like you have the unparsable string '...' somewhere in your Series, and that the data needs to be cleaned further.

Upvotes: 5

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