How change to the NaN type?-CodePudding

I have a data set that contains '-' and 'na' value. How to convert the data that are considered missing values to NAN by using the na_values attribute?

df = pd.read_csv('austin_weather.csv'.na_values==['na','-'])

CodePudding user response：

You code is not correct, try this:

import pandas as pd
from pprint import pprint

# test.csv:
# h1;h2;h3;h4
# test1;test2;-;na
    
# this is an incorrect syntax:
# df = pd.read_csv('test.csv'.na_values==['na','-'])
# >> AttributeError: 'str' object has no attribute 'na_values'

# correct usage of pandas read_csv():
df = pd.read_csv('test.csv', na_values=['na','-'], sep=';')
pprint(df)
# >>    h1     h2    h3  h4
# >> 0  test1  test2 NaN NaN

CodePudding user response：

Like Jeffrey Ram and Mortz explained in the comments, pandas.read_csv arguments need to be separated by a comma , and values have to be assigned by the equals sign =:

Use this instead :

df = pd.read_csv('austin_weather.csv', na_values=['na','-'])