Reputation: 106
Very basic question: what is the easiest way (least code) to generate a set of column names for a pandas dataframe when I would like to get 20 columns with names: s1, s2, s3, ... ,s20?
Upvotes: 3
Views: 3199
Reputation: 394279
You can use a list comprehension to generate the column names:
In [66]:
col_list = ['s' + str(x) for x in range(1,21)]
col_list
Out[66]:
['s1',
's2',
's3',
's4',
's5',
's6',
's7',
's8',
's9',
's10',
's11',
's12',
's13',
's14',
's15',
's16',
's17',
's18',
's19',
's20']
After which you can either pass this as the column
arg in DataFrame
ctor:
In [70]:
df = pd.DataFrame(np.random.randn(5,20), columns=col_list)
df.columns
Out[70]:
Index(['s1', 's2', 's3', 's4', 's5', 's6', 's7', 's8', 's9', 's10', 's11',
's12', 's13', 's14', 's15', 's16', 's17', 's18', 's19', 's20'],
dtype='object')
Or just overwrite the columns
attribute by assigning directly:
In [71]:
df = pd.DataFrame(np.random.randn(5,20))
df.columns = col_list
df.columns
Out[71]:
Index(['s1', 's2', 's3', 's4', 's5', 's6', 's7', 's8', 's9', 's10', 's11',
's12', 's13', 's14', 's15', 's16', 's17', 's18', 's19', 's20'],
dtype='object')
You can also use rename
or rename_axis
but they're for overwriting pre-existing column names for which there is already a related post
You can also add a prefix to a Series created from a range:
In [76]:
col_list = 's' + pd.Series(np.arange(1,21)).astype(str)
df.columns= col_list
df.columns
Out[76]:
Index(['s1', 's2', 's3', 's4', 's5', 's6', 's7', 's8', 's9', 's10', 's11',
's12', 's13', 's14', 's15', 's16', 's17', 's18', 's19', 's20'],
dtype='object')
Upvotes: 6