Update 03.04-Missing-Values.ipynb

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Abhinav sharma 2020-10-01 14:08:46 +05:30 committed by GitHub
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"## Operating on Null Values\n",
"\n",
"As we have seen, Pandas treats ``None`` and ``NaN`` as essentially interchangeable for indicating missing or null values.\n",
"To facilitate this convention, there are several useful methods for detecting, removing, and replacing null values in Pandas data structures.\n",
"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",
"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",
"They are:\n",
"\n",
"- ``isnull()``: Generate a boolean mask indicating missing values\n",