check for missing/ nan values in pandas dataframe
In [27]: df
Out[27]:
A B C
1 NaN -2.027325 1.533582
2 NaN NaN 0.461821
3 -0.788073 NaN NaN
4 -0.916080 -0.612343 NaN
5 -0.887858 1.033826 NaN
In [28]: df.isnull().sum() # Returns the sum of NaN values in each column.
Out[28]:
A 2
B 2
C 3
In [29]: df.isnull().sum().sum # Returns the total NaN values in the dataframe
Out[29]:
7missing values in a dataset python
df.isnull().sum()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)getting the number of missing values in pandas
cols_to_delete = df.columns[df.isnull().sum()/len(df) > .90]
df.drop(cols_to_delete, axis = 1, inplace = True)Copyright © 2021 Codeinu
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