I am a complete newbie at Python, and I'm struggling despite having Googled for quite a while. I know it should not be this difficult. I have a Dataframe called abc that looks like this:
PO_DATE PO_ITEM_NUMBER PO_PRICE PO_QTY
----------------------------------------------------------------
0 01/15/2017 ABC123 1.55 1000
1 01/25/2017 DEF456 5.55 500
I know the max PO_PRICE = 5.55, which I can find using:
max_PO_Price = abc["PO_PRICE"].max()
All I want to be able to do is identify which row has the max PO_PRICE, locate the PO_QTY field for that row, and decrement it by 100. I keep wanting to envision this dataframe is a 2-D array, but, it's not liking that, and, I know it's not an array, as there are different data types involved. I've been screwing this up now for too long, so, finally decided to post. I hope someone can forgive my lack of knowledge and point me in the right direction.
Thanks.
I think you want:
abc.loc[abc.PO_PRICE == abc["PO_PRICE"].max(), ['PO_QTY']] = abc['PO_QTY']-100
An example below:
# Import pandas
import pandas as pd
# Create dataframe from example and priunt
abc = pd.DataFrame({'PO_Date':['01/15/2017', '01/25/2017'], 'PO_ITEM_NUMBER': ['ABC123', 'DEF456'], 'PO_PRICE':[1.55, 5.55], 'PO_QTY':[1000, 500]})
print(abc)
# Find which row has the max PO Price, and then subtract the quantity by 100
abc.loc[abc.PO_PRICE == abc['PO_PRICE'].max(), ['PO_QTY']] = abc['PO_QTY']-100
# Print it out
print(abc)
Yields:
PO_Date PO_ITEM_NUMBER PO_PRICE PO_QTY
0 01/15/2017 ABC123 1.55 1000
1 01/25/2017 DEF456 5.55 500
PO_Date PO_ITEM_NUMBER PO_PRICE PO_QTY
0 01/15/2017 ABC123 1.55 1000
1 01/25/2017 DEF456 5.55 400
You should consider looking at this post, which my answer was influenced from. Additionally, the documentation on .loc might be helpful.