Environment variables are accessed through os.environ
import os
print(os.environ['HOME'])
Or you can see a list of all the environment variables using:
os.environ
As sometimes you might need to see a complete list!
# using get will return `None` if a key is not present rather than raise a `KeyError`
print(os.environ.get('KEY_THAT_MIGHT_EXIST'))
# os.getenv is equivalent, and can also give a default value instead of `None`
print(os.getenv('KEY_THAT_MIGHT_EXIST', default_value))
The Python default installation location on Windows is C:\Python
. If you want to find out while running python you can do:
import sys
print(sys.prefix)
RENAME SPECIFIC COLUMNS
Use the df.rename()
function and refer the columns to be renamed. Not all the columns have to be renamed:
df = df.rename(columns={'oldName1': 'newName1', 'oldName2': 'newName2'})
# Or rename the existing DataFrame (rather than creating a copy)
df.rename(columns={'oldName1': 'newName1', 'oldName2': 'newName2'}, inplace=True)
Minimal Code Example
df = pd.DataFrame('x', index=range(3), columns=list('abcde'))
df
a b c d e
0 x x x x x
1 x x x x x
2 x x x x x
The following methods all work and produce the same output:
df2 = df.rename({'a': 'X', 'b': 'Y'}, axis=1) # new method
df2 = df.rename({'a': 'X', 'b': 'Y'}, axis='columns')
df2 = df.rename(columns={'a': 'X', 'b': 'Y'}) # old method
df2
X Y c d e
0 x x x x x
1 x x x x x
2 x x x x x
Remember to assign the result back, as the modification is not-inplace. Alternatively, specify inplace=True
:
df.rename({'a': 'X', 'b': 'Y'}, axis=1, inplace=True)
df
X Y c d e
0 x x x x x
1 x x x x x
2 x x x x x
From v0.25, you can also specify errors='raise'
to raise errors if an invalid column-to-rename is specified. See v0.25 rename()
docs.
REASSIGN COLUMN HEADERS
Use df.set_axis()
with axis=1
and inplace=False
(to return a copy).
df2 = df.set_axis(['V', 'W', 'X', 'Y', 'Z'], axis=1, inplace=False)
df2
V W X Y Z
0 x x x x x
1 x x x x x
2 x x x x x
This returns a copy, but you can modify the DataFrame in-place by setting inplace=True
(this is the default behaviour for versions <=0.24 but is likely to change in the future).
You can also assign headers directly:
df.columns = ['V', 'W', 'X', 'Y', 'Z']
df
V W X Y Z
0 x x x x x
1 x x x x x
2 x x x x x
Best Answer
You can use
.replace
. For example:or directly on the
Series
, i.e.df["col1"].replace(di, inplace=True)
.