Python | Pandas Series.valid()

Python is a great language for doing data analysis, primarily because of the fantastic ecosystem of data-centric python packages. Pandas is one of those packages and makes importing and analyzing data much easier. Pandas series is a One-dimensional ndarray with axis labels. The labels need not be unique but must be a hashable type. The object supports both integer- and label-based indexing and provides a host of methods for performing operations involving the index. Pandas Series.valid() function return the same Series object but without the null values.

Syntax: Series.valid(inplace=False, **kwargs) Parameter : inplace: boolean Returns : Series

Example #1: Use Series.valid() function to remove the null values from the given Series object. Python3

# importing pandas as pd
import pandas as pd

# Creating the Series
sr = pd.Series(['New York', 'Chicago', None, 'Toronto', 'Lisbon', 'Rio', 'Chicago', 'Lisbon'])

# Print the series
print(sr)

Output : Now we will use Series.valid() function to remove the null values from the given series object. Python3 1==

# return valid values
sr.valid()

Output : As we can see in the output, the Series.valid() function has returned a Series object containing all the valid value of the original series object on which it was called. Example #2: Use Series.valid() function to remove the null values from the given Series object. Python3

# importing pandas as pd
import pandas as pd

# Creating the Series
sr = pd.Series([100, 214, 325, 88, None, 325, None, 325, 100])

# Print the series
print(sr)

Output : Now we will use Series.valid() function to remove the null values from the given series object. Python3 1==

# return valid values
sr.valid()

Output : As we can see in the output, the Series.valid() function has returned a Series object containing all the valid value of the original series object on which it was called.