df = pd.DataFrame({'a':['Small', 'Medium', 'High']})
In [22]: df
Out[22]:
a
0 Small
1 Medium
2 High
[3 rows x 1 columns]
df.replace({'a' : { 'Medium' : 2, 'Small' : 1, 'High' : 3 }})
mapping_dict = {
'Android': 'Android',
'Chrome OS': 'Chrome OS',
'Linux': 'Linux',
'Mac OS': 'macOS',
'No OS': 'No OS',
'Windows': 'Windows',
'macOS': 'macOS'
}
laptops['os'] = laptops['os'].map(mapping_dict)
print(my_series)
import pandas as pd
df = pd.DataFrame([
[4, -9, 8],
[1, 2, -4],
[2, 2, -8],
[0, 7, -4],
[2, 5, 1]],
columns=['a', 'b', 'c'])
df = df.replace({'a':{1:11, 2:22}, 'b':{5:55, 2:22}})
print(df)
# Specify Patterns to remove
removal_list = '|'.join(['
','
',' ','
','>','<'])
# Replace each occurance with nothing ('') and replace the column
df['columnA'] = df['columnA'].str.replace(removal_list,'')
df['column name'] = df['column name'].replace(['1st old value','2nd old value',...],['1st new value','2nd new value',...])