df_count¶
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hhpy.ds.
df_count
(x: str, df: pandas.core.frame.DataFrame, hue: Optional[str] = None, sort_by_count: bool = True, top_nr: int = 5, x_base: Optional[float] = None, x_min: Optional[float] = None, x_max: Optional[float] = None, other_name: str = 'other', other_to_na: bool = False, na: Union[bool, str] = 'drop') → pandas.core.frame.DataFrame[source]¶ Create a DataFrame of value counts. Supports hue levels and is therefore useful for plots, for an application see
countplot()
Parameters: - x – Main variable, name of a column in the DataFrame or vector data
- df – Pandas DataFrame containing the data, other objects are implicitly cast to DataFrame
- hue – Name of the column to split by level [optional]
- sort_by_count – Whether to sort the DataFrame by value counts [optional]
- top_nr – Number of unique levels to keep when applying
top_n_coding()
[optional] - x_base – if supplied: cast x to integer multiples of x_base, useful when you have float data that would result in many unique counts for close numbers [optional]
- x_min – limit the range of valid numeric x values to be greater than or equal to x_min [optional]
- x_max – limit the range of valid numeric x values to be less than or equal to x_max [optional]
- other_name – Name of the levels grouped inside other [optional]
- other_to_na – Whether to cast all other elements to NaN [optional]
- na – whether to keep (True, ‘keep’) na values and implicitly cast to string or drop (False, ‘drop’) them [optional]
Returns: pandas DataFrame containing the counts by x (and by hue if it is supplied)