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Method 1: Selecting rows of Pandas Dataframe based on particular column value using ‘>’, ‘=’, ‘=’, ‘<=’, ‘!=’ operator.
Example 1: Selecting all the rows from the given Dataframe in which ‘Percentage’ is greater than 75 using [ ].
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Example 2: Selecting all the rows from the given Dataframe in which ‘Percentage’ is greater than 70 using loc[ ].
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Method 2: Selecting those rows of Pandas Dataframe whose column value is present in the list using isin() method of the dataframe.
Example 1: Selecting all the rows from the given dataframe in which ‘Stream’ is present in the options list using [ ].
Output:
Example 2: Selecting all the rows from the given dataframe in which ‘Stream’ is present in the options list using loc[ ].
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Method 3: Selecting rows of Pandas Dataframe based on multiple column conditions using ‘&’ operator.
Example1: Selecting all the rows from the given Dataframe in which ‘Age’ is equal to 22 and ‘Stream’ is present in the options list using [ ].
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Example 2: Selecting all the rows from the given Dataframe in which ‘Age’ is equal to 22 and ‘Stream’ is present in the options list using loc[ ].
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