# method A
df = df.set_index('col')
# method B
df['col'] = df.index
# assignment copy
df = df.set_index('month')
# or inplace
df.set_index('month', inplace=True)
# year sale month month year sale
# 0 2012 55 1 1 2012 55
# 1 2014 40 4 => 4 2014 40
# 2 2013 84 7 7 2013 84
# 3 2014 31 10 10 2014 31
df.reset_index(inplace=True)
df = df.rename(columns = {'index':'new column name'})
df.set_index(['col1', 'col2'])
# Create a Pandas dataframe
df = pd.DataFrame({'A':[1, 2, 3, 4],
'B':[5, 6, 7, 8]})
# Rename index values for each row
df.set_axis(['Row_1', 'Row_2', 'Row_3', 'Row_4'], axis = 'index', inplace = True)
df.set_index('month')
>>> college_idx = college.set_index('instnm')>>> sats = college_idx[['satmtmid', 'satvrmid']].dropna()>>> sats.head()
Pandas dataframe set-index
Pandas dataframe set-index()
Pandas dataframe set-index
Pandas dataframe set-index
Pandas dataframe set-index
>>> df.index = [x for x in range(1, len(df.values)+1)]
>>> df
name job score
1 'Pete Houston' 'Software Engineer' 92
2 'John Wick' 'Assassin' 95
3 'Bruce Wayne' 'Batman' 99
4 'Clark Kent' 'Superman' 96
Pandas dataframe set-index()
Pandas dataframe set-index()