remove rows or columns with NaN value
df.dropna() #drop all rows that have any NaN values
df.dropna(how='all')remove rows or columns with NaN value
df.dropna() #drop all rows that have any NaN values
df.dropna(how='all')handling missing dvalues denoted by a '?' in pandas
# Making a list of missing value typesmissing_values = ["n/a", "na", "--"]df = pd.read_csv("property data.csv", na_values = missing_values)Copyright © 2021 Codeinu
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