Python Pandas Filter Missing data Tutorial-11

Published: 10 August 2016
on channel: MyStudy

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This video will explain how to filter missing data from series and dataframe data structure of pandas.

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coding: utf-8

# Filter Missing data
Data = pd.Series([1,np.NAN,4,5,np.NAN,6])
data1 = pd.DataFrame([[5., 2.9, 8.], [1.5, np.NAN, np.NAN],[np.NAN, np.NAN, np.NAN], [np.NAN, 6.2, 23.]])
df = pd.DataFrame(np.random.randn(4, 3))

# Row level Drop
import pandas as pd
import numpy as np

Data = pd.Series([1,np.NAN,4,5,np.NAN,6])
Data
Data.dropna()

data1 = pd.DataFrame([[5., 2.9, 8.], [1.5, np.NAN, np.NAN],[np.NAN, np.NAN, np.NAN], [np.NAN, 6.2, 23.]])
data1

data1.dropna()
data1.dropna(how='all')

# Column Level Drop

data1
data1.dropna(axis=1)
data1.dropna(axis=1, how='all')

# Filter Based on thresold
data1.dropna(thresh=1)
data1.dropna(thresh=2)

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