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Pandas Series: transform() function

Call function on self producing a Series in Pandas

The transform() function is used to call function on self producing a Series with transformed values and that has the same axis length as self.

Syntax:

Series.transform(self, func, axis=0, *args, **kwargs)
Pandas Series transform image

Parameters:

Name Description Type/Default Value Required / Optional
func Function to use for transforming the data. If a function, must either work when passed a Series or when passed to Series.apply.
Accepted combinations are:

  • function
  • string function name
  • list of functions and/or function names, e.g. [np.exp. 'sqrt']
  • dict of axis labels -> functions, function names or list of such.
unction, str, list or dict Required
axis Parameter needed for compatibility with DataFrame {0 or ‘index’} Required
args Positional arguments to pass to func.   Required
**kwds Keyword arguments to pass to func.   Required

Returns:Series
A Series that must have the same length as self.

Raises: ValueError- If the returned Series has a different length than self.

Example:

Python-Pandas Code:

import numpy as np
import pandas as pd
df = pd.DataFrame({'P': range(4), 'Q': range(2, 6)})
df

Output:

   P  Q
0  0  2
1  1  3
2  2  4
3  3  5
Pandas Series transform image

Python-Pandas Code:

import numpy as np
import pandas as pd
df = pd.DataFrame({'P': range(4), 'Q': range(2, 6)})
df.transform(lambda x: x + 2)

Output:

   P	Q
0	2	4
1	3	5
2	4	6
3	5	7

Example - Even though the resulting Series must have the same length as the input Series, it is possible to provide several input functions:

Python-Pandas Code:

import numpy as np
import pandas as pd
s = pd.Series(range(4))
s

Output:

0    0
1    1
2    2
3    3
dtype: int64

Python-Pandas Code:

import numpy as np
import pandas as pd
s = pd.Series(range(4))
s.transform([np.sqrt, np.exp])

Output:

      sqrt	     exp
0	0.000000	1.000000
1	1.000000	2.718282
2	1.414214	7.389056
3	1.732051	20.085537

Previous: Aggregation with pandas series
Next: Map values of Pandas Series



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https://w3resource.com/pandas/series/series-transform.php