Create a new column in Dataframe based on condition being check. I want to check value of a column for multiple values and then assign it a value

Asked Jan 15 '21 at 05:41

Active Jan 15 '21 at 05:41

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Here is what I am doing now:

df1.loc[df1['Product'] == "Bat",'Category'] = "Sports"
df1.loc[df1['Product'] == "Medicine",'Category'] = "Pharma"
df1.loc[df1['Product'] == "shoes",'Category'] = "Fashion"

But now I need to perform the check for other stuff also using the same line i.e like a ball, clothes, etc

df1.loc[df1['Product'] == ["Bat" or "Ball"],'Category'] = "Sports"

While doing this getting below error: ValueError: The truth value of a Series is ambiguous. Use a.empty, a.bool(), a.item(), a.any() or a.all().

Is there any better way for the same, I want to perform the check on a large number of products?

asked Jan 15 '21 at 05:41

Luthor_

1

`df1['Product'].isin(['Bat', 'Ball'])`. – Quang Hoang Jan 15 '21 at 05:43
1

and also consider `np.select` for multiple conditions. Also `map` would work pretty well. – Quang Hoang Jan 15 '21 at 05:45

Create a new column in Dataframe based on condition being check. I want to check value of a column for multiple values and then assign it a value

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