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#21 Dealing with missing data | Python for Data Science
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Welcome to 'Python for Data Science' course !
In this video you'll discover effective strategies for handling the pervasive issue of missing values in your datasets. The video explores the common practice of imputing missing values using the mean or median, emphasizing the importance of understanding your data's distribution and choosing the appropriate measure. You'll learn how to use Python's `describe()` function to gain insights into your data's characteristics and make informed imputation decisions.
NPTEL Courses permit certifications that can be used for Course Credits in Indian Universities as per the UGC and AICTE notifications.
#MissingValues #Imputation #MeanImputation #Median Imputation #ModeImputation #describe
In this video you'll discover effective strategies for handling the pervasive issue of missing values in your datasets. The video explores the common practice of imputing missing values using the mean or median, emphasizing the importance of understanding your data's distribution and choosing the appropriate measure. You'll learn how to use Python's `describe()` function to gain insights into your data's characteristics and make informed imputation decisions.
NPTEL Courses permit certifications that can be used for Course Credits in Indian Universities as per the UGC and AICTE notifications.
#MissingValues #Imputation #MeanImputation #Median Imputation #ModeImputation #describe
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