在 Pandas (Python 3) 中用 0 替换 WhiteSpace

Question

simple question here -- how do I replace all of the whitespaces in a column with a zero?

For example:

  Name       Age
  John       12
  Mary 
  Tim        15

into

  Name       Age
  John       12
  Mary       0
  Tim        15

I've been trying using something like this but I am unsure how Pandas actually reads whitespace:

 merged['Age'].replace(" ", 0).bfill()

Any ideas?

Answer 1

Use the built in method convert_objects and set param convert_numeric=True :

In [12]:
# convert objects will handle multiple whitespace, this will convert them to NaN
# we then call fillna to convert those to 0
df.Age = df[['Age']].convert_objects(convert_numeric=True).fillna(0)
df
Out[12]:
   Name  Age
0  John   12
1  Mary    0
2   Tim   15

Answer 2

Here's an answer modified from this, more thorough question . I'll make it a little bit more Pythonic and resolve your basestring issue.

def ws_to_zero(maybe_ws):
    try:
        if maybe_ws.isspace():
            return 0
        else:
            return maybe_ws
    except AttributeError:
        return maybe_ws

d.applymap(ws_to_zero)

where d is your dataframe.

Answer 3

merged['Age'] = merged['Age'].apply(lambda x: 0 if x == ' ' else x)

Answer 4

if you want to use NumPy, then you can use the below snippet:

import numpy as np    
df['column_of_interest'] = np.where(df['column_of_interest']==' ',0,df['column_of_interest']).astype(float)

While Paulo's response is excellent, my snippet above may be useful when multiple criteria are required during advanced data manipulation.