PYTHON

pandas replace data in specific columns with specific values

### replace one value ###
df["column"].replace("US","UK") # you can also use numerical values
### replace more than one value ###
df["column"].replace(["man","woman","child"],[1,2,3]) # you can also use numerical values
#   man ==> 1
# woman ==> 2
# child ==> 3

replace value in dataframe

# this will replace "Boston Celtics" with "Omega Warrior"
df.replace(to_replace ="Boston Celtics",
                 value ="Omega Warrior")

Change one value based on another value in pandas

df.loc[df.ID == 103, ['FirstName', 'LastName']] = 'Matt', 'Jones'
//or
import pandas
df = pandas.read_csv("test.csv")
df.loc[df.ID == 103, 'FirstName'] = "Matt"
df.loc[df.ID == 103, 'LastName'] = "Jones"

pandas replace values from another dataframe

In [36]:
df['Group'] = df['Group'].map(df1.set_index('Group')['Hotel'])
df

Out[36]:
         Date  Group  Family  Bonus
0  2011-06-09  Jamel  Laavin    456
1  2011-07-09  Frank  Grendy    679
2  2011-09-10   Luxy  Fantol    431
3  2011-11-02  Frank  Gondow    569