Pandas Functions
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df.groupby('column_name').agg({'another_column': 'mean'})
aggregate a measure based on a dimension
df.isnull().sum()
in Pandas is used to count the number of missing (null or NaN) values in each column of a DataFrame
df.describe()
method in Pandas generates descriptive statistics for a DataFrame. It provides a high-level summary of the central tendency, dispersion, and shape of a dataset's distribution
df.dropna()
method in pandas is used to remove missing values (represented as NaN or None) from a DataFrame. By default, it removes rows that contain at least one missing value.
df.iloc[row_index, col_index]
syntax in Pandas is used to select a specific element from a DataFrame based on its integer-location-based index
