How to specify multiple NA values?

To specify multiple NA values when reading a CSV file using pandas.read_csv(), you can pass a list of strings to the na_values parameter. Each string in the list will be treated as a representation of a missing value (NaN) in the resulting DataFrame.

Example:

Suppose you have a CSV file named data.csv that contains various representations of missing values:

column1,column2,column3
1,2,3
4,NA,6
7,8,?
9,,10

In this example, the missing values are represented by NA, ?, and empty strings. You can specify all these representations as NA values like this:

import pandas as pd

# Read the CSV file and specify multiple NA values
df = pd.read_csv('data.csv', na_values=['NA', '?', ''])

print(df)

Output:

   column1  column2  column3
0        1      2.0      3.0
1        4      NaN      6.0
2        7      8.0      NaN
3        9      NaN     10.0

In this output, the NA, ?, and empty string values in the DataFrame are replaced with NaN, allowing you to handle missing data effectively.