Is here a way to loop through dataframe in PANDAS and multiply by 2 different conditions?

Question

Essentially I am working with a dataframe and I am trying to multiply by 2 different conditions. If the value in order description == Internet Port Charge it needs to be multiplied in the amount column by .33 and if not then by 1.9. I keep getting a value error. Thank you!

for x in max_sales:
if max_sales['Order description'] == 'Internet Port Charge':
    max_sales['amount'] * .33
else:
    max_sales['amount'] * 111.9

 1 for x in max_sales:
----> 2     if max_sales['Order description'] == 'Internet Port Charge':
  3         max_sales['amount'] * .33
  4     else:
  5         max_sales['amount'] * 111.9

~\Anaconda3\lib\site-packages\pandas\core\generic.py in __nonzero__(self)
   1535     @final
   1536     def __nonzero__(self):
-> 1537         raise ValueError(
   1538             f"The truth value of a {type(self).__name__} is ambiguous. "
   1539             "Use a.empty, a.bool(), a.item(), a.any() or a.all()."

to iterate over dataframe rows, use iterrows(), here is an example https://stackoverflow.com/questions/16476924/how-to-iterate-over-rows-in-a-dataframe-in-pandas — Naveed, Jun 02 '22 at 15:05
Write your condition as in a function, e.g., `def func(x): if x['amount'] ... return ...` then use the `apply` function to apply the function. — MYousefi, Jun 02 '22 at 15:05

score 1 · Answer 1 · answered Jun 02 '22 at 15:14

You could use NumPy's .where():

import numpy as np

max_sales['amount'] = np.where(
    max_sales['Order description'] == 'Internet Port Charge',
    max_sales['amount'] * .33,
    max_sales['amount'] * 111.9
)

This looks for rows where the condition is met and multiplies those values by 0.33. Where the condition is False, it multiplies by 111.9. It's also significantly faster (and cleaner) than iterating over the DataFrame.

score 0 · Answer 2 · answered Jun 02 '22 at 15:08

If you just have these conditions, then .loc the parts that you want to multiply by an amount, then assign them that amount:

max_sales.loc[max_sales['Order description'] == 'Internet Port Charge']['amount'] = max_sales.loc[max_sales['Order description'] == 'Internet Port Charge']['amount']*0.33

max_sales.loc[~(max_sales['Order description'] == 'Internet Port Charge')]['amount'] = max_sales.loc[~(max_sales['Order description'] == 'Internet Port Charge')]['amount']*1.9

I don't see what the for x in max_sales is supposed to do, seeing as x isn't used again later.

Robert Haynes · Answer 3 · 2022-06-02T15:16:46.803

0

for index, row in df.iterrows():
if row['Order description'] == 'Internet Port Charge':
    row['amount'] = row['amount'] * 0.33
else:
    row['amount'] = row['amount'] * 111.9

You must loop through the DataFrame using .iterrows() then you can access each row individually

.iterrows() is very resource intensive though.

edited Jun 02 '22 at 15:16

answered Jun 02 '22 at 15:15

Robert Haynes

1
2

score 0 · Answer 4 · answered Jun 02 '22 at 15:46

You can use apply and lambda:

import pandas as pd


# Set up dummy data
df = [
    ["Internet Port Change", 20],
    ["Foobar", 20]
]
df = pd.DataFrame(df, columns=["Order description", "amount"])
#       Order description  amount
# 0  Internet Port Change      20
# 1                Foobar      20


# Use apply and lambda
df["amount"] = df.apply(
    lambda x: x["amount"]*0.33 if x["Order description"] == "Internet Port Change" \
        else x["amount"]*111.9,
    axis=1)
#       Order description  amount
# 0  Internet Port Change     6.6
# 1                Foobar  2238.0

Is here a way to loop through dataframe in PANDAS and multiply by 2 different conditions?

4 Answers4