替换熊猫数据框列中的当前值（NA / NaN除外）

Question

There is a fillna method for filling missing values, but is there a method for replacing all the actual values with a given value.

For example:

      c
  0  NA/NaN
  1  2.0
  2  NA/NaN
  3  6.0
  4  8.0
  5  NA/NaN
  6  12.0

For every data point, I would like to mark it with 'v' meaning that it contains a valid value:

      c
  0   NA/NaN
  1  'v'
  2   NA/NaN
  3  'v'
  4  'v'
  5   NA/NaN
  6  'v'

Answer 1

• Is there a specific reason why you want to overwrite the existing value, instead of keeping a separate series or column of validity ?
• And using a custom marker instead of a boolean value is also an extra complexity.

Further down in your code it would be easier to simply us

valid = df['c'].notnull()

if you really want to overwrite it with a marker string:

df.loc[df['c'].notnull(), 'c'] = 'v'

Answer 2

试试这个：

df.loc[~df['c'].isnull()] = "'v'"