Iterate dataframe in pandas looking for a string and generate new column

Question

I have the following dataframe:

      import pandas as pd
      df = pd.DataFrame({'Id_Sensor': [1, 2, 3, 4],'Old_Column': ['P55X', 'MEC8901', 'P58Y', 'M59X']})

      print(df)

        Id_Sensor   Old_Column
           1           P55X
           2           MEC8901
           3           P58Y
           4           M59X

I need to create a new column on this dataframe. If the first letter is P, the column should receive 'computer_typeA'. If the first three letters are MEC the column should receive 'computer_typeB'

I tried to do the following:

        #This code segment is incorrect
        for i in range(0, len(df)):

          if(df['Old_Column'].iloc[i][:1] == 'P'):
               df['New_Column'].iloc[i] == 'computer_typeA'

         elif(df['Old_Column'].iloc[i][:3] == 'MEC'):
               df['New_Column'].iloc[i] == 'computer_typeB'

         else:
               df['New_Column'].iloc[i] == 'computer_other'

The answer is incorrect:

      print(df)
        Id_Sensor   Old_Column  New_Column
           1           P55X       Nan
           2          MEC8901     Nan
           3           P58Y       Nan
           4           M59X       Nan

I would like the answer to be like this:

        Id_Sensor   Old_Column       New_Column
           1           P55X       computer_typeA
           2          MEC8901     computer_typeB
           3           P58Y       computer_typeA
           4           M59X       computer_other

sammywemmy · Accepted Answer · 2020-01-30 23:17:43Z

2

You can use numpy.select for conditional statements:

cond1 = df.Old_Column.str.startswith('P')
cond2 = df.Old_Column.str.startswith('MEC')
condlist = [cond1,cond2]
choicelist = ['computer_typeA', 'computer_typeB']
df['New Column'] = np.select(condlist,choicelist)
df['New Column'] = df['New Column'].replace('0','computer_other')

   Id_Sensor    Old_Column  New Column
0   1   P55X    computer_typeA
1   2   MEC8901 computer_typeB
2   3   P58Y    computer_typeA
3   4   M59X    computer_other

answered Jan 30, 2020 at 23:17

sammywemmy

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Comments

nizarcan · Accepted Answer · 2020-01-30 23:33:33Z

0

This simple code should do the work:

df["New_Column"] = "computer_other"

df.loc[df.Old_Column.apply(lambda x: x[0] == "P"), "New_Column"] = "computer_typeA"

df.loc[df.Old_Column.apply(lambda x: x[:3] == "MEC"), "New_Column"] = "computer_typeB"

Note: The reason of the initial declaration of New_Column as computer_other is to simplify the process.

Hope this helps.

edited Jan 30, 2020 at 23:33

answered Jan 30, 2020 at 23:14

nizarcan

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2 Comments

nizarcan Over a year ago

Also, if you found the answer useful, please upvote the answer and click on the tick that is next to the answer if the answer is what you're looking for.

Georgina Skibinski Over a year ago

Please avoid using apply(...): stackoverflow.com/a/54432584/11610186

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