How can i pivot down my row values for each row in pandas dataframe? [closed]

Answer 1

You can use stack, reset_index and rename column 0:

print df.set_index(['Name', 'Percent']).stack().reset_index(level=[0,1])
                                       .reset_index(drop=True).rename(columns={0:'Subject'})
     Name  Percent  Subject
0  ramesh       85    Maths
1  ramesh       85  Science
2     ram       42    Maths
3     Raj       85  Science

Answer 2

pd.lreshape can combine the values from multiple columns into one:

import numpy as np
import pandas as pd
nan = np.nan
df = pd.DataFrame({'Name': ['ramesh', 'ram', 'Raj'],
                   'Percent': [85, 42, 85],
                   'Subject1': ['Maths', 'Maths', nan],
                   'Subject2': ['Science', nan, 'Science']})

print(pd.lreshape(df, {'Subject':['Subject1', 'Subject2']}))

yields

     Name  Percent  Subject
0  ramesh       85    Maths
1     ram       42    Maths
2  ramesh       85  Science
3     Raj       85  Science

---

pd.lreshape does not appear to be documented (yet?) in the online docs. Here is its docstring:

In [40]: help(pd.lreshape)
Help on function lreshape in module pandas.core.reshape:

lreshape(data, groups, dropna=True, label=None)
    Reshape long-format data to wide. Generalized inverse of DataFrame.pivot

    Parameters
    ----------
    data : DataFrame
    groups : dict
        {new_name : list_of_columns}
    dropna : boolean, default True

    Examples
    --------
    >>> import pandas as pd
    >>> data = pd.DataFrame({'hr1': [514, 573], 'hr2': [545, 526],
    ...                      'team': ['Red Sox', 'Yankees'],
    ...                      'year1': [2007, 2008], 'year2': [2008, 2008]})
    >>> data
       hr1  hr2     team  year1  year2
    0  514  545  Red Sox   2007   2008
    1  573  526  Yankees   2007   2008

    >>> pd.lreshape(data, {'year': ['year1', 'year2'], 'hr': ['hr1', 'hr2']})
          team   hr  year
    0  Red Sox  514  2007
    1  Yankees  573  2007
    2  Red Sox  545  2008
    3  Yankees  526  2008

    Returns
    -------
    reshaped : DataFrame