Below is an example that performs lexicographic sort on a dataframe. The idea is to create an numerical index based on the specific sort. Then to perform a numerical sort based on the index. A column is added to the dataframe to do so, and is then removed.

import pandas as pd

# Create DataFrame
df = pd.DataFrame(
{'id':[2967, 5335, 13950, 6141, 6169],
    'Player': ['Cedric Hunter', 'Maurice Baker',
               'Ratko Varda' ,'Ryan Bowen' ,'Adrian Caldwell'],
    'Year': [1991, 2004, 2001, 2009, 1997],
    'Age': [27, 25, 22, 34, 31],
    'Tm': ['CHH' ,'VAN' ,'TOT' ,'OKC', 'DAL'],
    'G': [6, 7, 60, 52, 81]})

# Define the sorter
sorter = ['TOT', 'ATL', 'BOS', 'BRK', 'CHA', 'CHH', 'CHI', 'CLE', 'DAL','DEN',
          'DET', 'GSW', 'HOU', 'IND', 'LAC', 'LAL', 'MEM', 'MIA', 'MIL',
          'MIN', 'NJN', 'NOH', 'NOK', 'NOP', 'NYK', 'OKC', 'ORL', 'PHI',
          'PHO', 'POR', 'SAC', 'SAS', 'SEA', 'TOR', 'UTA', 'VAN',
          'WAS', 'WSB']

# Create the dictionary that defines the order for sorting
sorterIndex = dict(zip(sorter, range(len(sorter))))

# Generate a rank column that will be used to sort
# the dataframe numerically
df['Tm_Rank'] = df['Tm'].map(sorterIndex)

# Here is the result asked with the lexicographic sort
# Result may be hard to analyze, so a second sorting is
# proposed next
## NOTE: 
## Newer versions of pandas use 'sort_values' instead of 'sort'
df.sort_values(['Player', 'Year', 'Tm_Rank'],
        ascending = [True, True, True], inplace = True)
df.drop('Tm_Rank', 1, inplace = True)
print(df)

# Here is an example where 'Tm' is sorted first, that will 
# give the first row of the DataFrame df to contain TOT as 'Tm'
df['Tm_Rank'] = df['Tm'].map(sorterIndex)
## NOTE: 
## Newer versions of pandas use 'sort_values' instead of 'sort'
df.sort_values(['Tm_Rank', 'Player', 'Year'],
        ascending = [True , True, True], inplace = True)
df.drop('Tm_Rank', 1, inplace = True)
print(df)

My problem, fyi, was that I wasn't returning the resulting dataframe, so PyCharm wasn't bothering to update said dataframe. Naming the dataframe after the return keyword fixed the issue.

Edit: I had return at the end of my method instead of return df, which the debugger must of noticed, because df wasn't being updated in spite of my explicit, in-place sort.