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Update 03.04-Missing-Values.ipynb
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"## Operating on Null Values\n",
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"As we have seen, Pandas treats ``None`` and ``NaN`` as essentially interchangeable for indicating missing or null values.\n",
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"To facilitate this convention, there are several useful methods for detecting, removing, and replacing null values in Pandas data structures.\n",
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"To facilitate this convention, there are several useful methods for detecting, removing, and replacing null values in Pandas data structures. Also some of the times if we drop the data \n",
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"Then it could create skewness among data so we use filling techniques like using mean, median values to fill out the data which will create a normal distribution behaviour among data. :\n",
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"They are:\n",
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"\n",
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"- ``isnull()``: Generate a boolean mask indicating missing values\n",
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