replace the existing values to NAN in a given .csv file

user_14003174 0
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Hi there I'm a newbie in python learning through notebook, I have given iris dataset through .csv file and asked to replace one of the column values in some particular rows to NaN.I have tried "fillna" functions and "replace" functions but I'm not successful.Here is my code:

import pandas as pd
import numpy as np
from numpy import nan as NaN
url = 'https://archive.ics.uci.edu/ml/machine-learning-databases/iris/iris.data'
iris = pd.read_csv(url)
iris.columns = ['sepal_length','sepal_width','petal_length','petal_width','class']
iris.columns

#iris

iris.petal_length.fillna(np.nan)
iris1=iris.iloc[10:30]
print (iris1)
#bool_series = pd.isnull(iris['petal_length'])
#print (df)
pandas numpy python
2 Answers

Looks like the problem is, that you are not saving the resulting DataFrame from .fillna() or .replace(). By default, those methods return new DataFrame object. To fix this either save the result to a variable or use inplace=True argument in your replace() or fillna() calls.

user_90513030

I think you can use:

This replaces <some_value> with np.nan for the petal_length column

irirs.petal_length.replace(<some_value>, np.nan)

This will replace the rows where petal_length is equal to <some_value>

irirs[irirs.petal_length == <some_value>] = np.nan
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