pythonpandasdataframeconceptual

Efficient way to replace a large number of entries in a dataframe

I'm creating an automation program for work that automatically takes care of generating our end of the the month reports. The challenge I've run into is thinking of an efficient way to make a large number of replacements without a for loop and a bunch of if statements.

I have a file that's about 113 entries long giving me instructions on which entries need to be replaced with another entry

Uom Actual UOM
0 ML
3 ML
4 UN
7 ML
11 ML
12 ML
19 ML
55 ML
4U GR

There is a large number of duplicates where I change the values to the same thing (3,7,11 etc change to ML) but it still seems like I'd have to loop through a decent amount of if statements for every cell. I'd probably use a switch statement for this in another language but python doesn't seem to have them.

Pseudocode for what I'm thinking:

for each in dataframe
   if (3,7,11, etc...)
      change cell to ML
   if (4)
      change cell to UN
   if (4U)
      change cell to GR
etc.

Is there a more efficient way to do this or am I on the right track?

Solution

  • I would create a dictionary from your mapping_df (I assume the dataframe you posted is called mapping_df), and then map the result in your main dataframe.

    This way you won't need to manually declare anything, so even if new rows are added in the 113 rows mapping_df, the code will still work smoothly:

    # Create a dictionary with your Uom as Key
d = dict(zip(mapping_df.Uom,mapping_df['Actual UOM']))

# And then use map on your main_df Uom column 
main_df['Actual Uom'] = main_df['Uom'].map(d)

    Something like the above should work.