pandas replace values from another dataframe
pandas replace values from another dataframe
xxxxxxxxxxIn [36]:df['Group'] = df['Group'].map(df1.set_index('Group')['Hotel'])dfOut[36]: Date Group Family Bonus0 2011-06-09 Jamel Laavin 4561 2011-07-09 Frank Grendy 6792 2011-09-10 Luxy Fantol 4313 2011-11-02 Frank Gondow 569Source: stackoverflow.com
Closely Related Answers
xxxxxxxxxx# Replace missing valuesdf["col"].replace(np.nan, new_val)# Replace other valuesdf["col"].str.replace('old','new')# Replace using maskingdf.loc[df['col']=='old', 'col'] = 'new'# Replace all specified value in the dataframedf_replaced = df.replace(1, 0)Source: Grepper
xxxxxxxxxx### 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 ==> 3Source: Grepper
xxxxxxxxxx# replace() syntaxDataFrame.replace(to_replace="<the_value_you_want_to_replace>", value="<new_value_for_input>", inplace=False, limit=None, regex=False, method='pad')Source: sparkbyexamples.com
xxxxxxxxxxdf.loc[df.ID == 103, ['FirstName', 'LastName']] = 'Matt', 'Jones'//orimport pandasdf = pandas.read_csv("test.csv")df.loc[df.ID == 103, 'FirstName'] = "Matt"df.loc[df.ID == 103, 'LastName'] = "Jones"Source: stackoverflow.com
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