CODEWITHSUNDEEP
pythonpandasint
Serdia
Serdia

Reputation: 4428

'int' object is not subscriptable. Pandas

I have dataset df. within this dataset I have column Gross I am completely new to Python,

enter image description here

I am trying to convert this column to float and display sum()

dollarGross = lambda x: float(x[1:-1])
df.Gross = df.Gross.apply(dollarGross)
df.Gross.sum()

But I am getting this error:

<ipython-input-294-a9010792122a> in <lambda>(x)
----> 1 dollarGross = lambda x: float(x[1:-1])
      2 df.Gross = df.Gross.apply(dollarGross)
      3 df.Gross.sum()

TypeError: 'int' object is not subscriptable

What am I missing?

Upvotes: 2

Views: 9026

Answers (4)

piRSquared
piRSquared

Reputation: 294338

Your error starts here:

df.Gross.apply(dollarGross)

df.Gross is a pandas.Series and when you use the apply method, pandas iterates through each member of the series and passes that member to the "callable" (also known as a function, more on this in a bit) named dollarGross. The critical thing to understand is what the members of the pandas.Series are. In this case, they are integers. So each integer in the series gets passed to dollarGross and gets called like this:

dollarGross(184)

This in turn looks like this:

float(184[1:-1])

Which makes no sense. You are trying to use [1:-1] which is subscripting/slicing syntax on an integer. And that is what the error is telling you: Hey, you can't subscript an integer!

That is why it's good to tell us what you are trying to do. Because now we can help you do that. Remember I said you can pass a "callable" to apply. Well, float is the name of the class of float objects... It's also a "callable" because we can do this float(184). So....

df.Gross.apply(float)

Should get things done. However, it's still probably better to do this

df.Gross.astype(float)

Or, if some of the members of df.Gross cannot be interpreted as a float value, it's probable better to use @MaxU's answer.

Upvotes: 3

MaxU - stand with Ukraine
MaxU - stand with Ukraine

Reputation: 210852

AFAIK pd.to_numeric() method provides us the most idiomatic way to convert strings to numerical values:

df['Gross'] = pd.to_numeric(df['Gross'], errors='coerce')
print(df['Gross'].sum())

Upvotes: 3

Dest
Dest

Reputation: 43

I think you should separate the columns using 

dollarGross = df['Gross'] #I defined a new array to store the Gross Values 
print(dollarGross.sum())

Upvotes: 0

knurzl
knurzl

Reputation: 356

I think you just have to write dollarGross = lambda x: float(x). If you use square brackets you try to access an array.

Upvotes: 2

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