用上下限改变值

Question

I have one dataset with several column: data-pioggia-name.....

I would like to rename values, within of the column pioggia. I would like:

• values<0 = 0
• values>400 = 0

I tried with:

data.loc[data.pioggia < 0]= "0"

But I have one problem with values > 400 = 0

Answer 1

To recap, I am guessing your DataFrame is called data and pioggia is the name of the column that serves as filter for the values to be changed.

If so, then the following code should do:

data.loc[(data['pioggia'] < 0) & (data['pioggia'] > 400)] = 0

Note that when you write "0" you are entering a string whose only character is 0 , not a number.

Which is the error that you're facing for values > 400, anyway?

EDIT: re-reading it, I think you wanted only the values in pioggia to be changed to 0. If so, replace data.loc with data['pioggia'].loc .

Answer 2

I share my code with some corrections:

import pandas as pd
data = pd.read_csv('name_dataset', sep=';')
data.info ()

data['pioggia']=data['pioggia'].fillna(0) #within dataset there is NAN
data['pioggia']=data['pioggia'].astype(int) #change value in int
data['pioggia'].loc[data.pioggia < 0]= 0 #change value<0 =0
data['pioggia'].loc[data.pioggia > 400]= 0 #change value>400 =0

# in my case I wanted to create the sum of the values, it is similar pivot table
x1_1=data.groupby('variable')[['pioggia']].sum()

or there is other solution, to get data inside interval. Getting 0<value<400

start=0
end=400
data['pioggia']=data['pioggia'].astype(int)
data.pioggia=(data['pioggia']>start)&(data['pioggia']<=end)