niimpy.exploration.eda.countplot module¶
Created on Mon Nov 8 14:42:18 2021
@author: arsii
- niimpy.exploration.eda.countplot.barplot_(df, fig_title, xlabel, ylabel)[source]¶
Plot a barplot showing counts for each subjects
A dataframe must have columns named ‘user’, containing the user id’s, and ‘values’ containing the observation counts.
- Parameters
- dfPandas Dataframe
Dataframe containing the data
- fig_titlestr
Plot title
- xlabelstr
Plot xlabel
- ylabelstr
Plot ylabel
- Returns
- niimpy.exploration.eda.countplot.boxplot_(df, fig_title, points='outliers', y='values', xlabel='Group', ylabel='Count', binning=False)[source]¶
Plot a boxplot
- Parameters
- dfPandas Dataframe
Dataframe containing the data
- fig_titlestr
Plot title
- pointsstr
If ‘all’, show all observations next to boxplots If ‘outliers’, show only outlying points The default is ‘outliers’
- y: str
A dataframe column to plot
- xlabelstr
Plot xlabel
- ylabelstr
Plot ylabel
- Returns
- niimpy.exploration.eda.countplot.calculate_bins(df, binning)[source]¶
Calculate time index based bins for each observation in the dataframe.
- Parameters
- dfPandas DataFrame
- binningstr
- to_stringbool
- Returns
- binspandas period index
- niimpy.exploration.eda.countplot.countplot(df, fig_title, plot_type='count', points='outliers', aggregation='group', user=None, column=None, binning=False)[source]¶
Create boxplot comparing groups or individual users.
- Parameters
- dfpandas DataFrame
A DataFrame to be visuliazed
- fig_titlestr
The plot title.
- plot_typestr
If ‘count’, plot observation count per group (boxplot) or by user (barplot) If ‘value’, plot observation values per group (boxplot) The default is ‘count’
- aggregationstr
If ‘group’, plot group level summary If ‘user’, plot user level summary The default is ‘group’
- userstr
if given … The default is None
- columnstr, optional
if None, count number of rows. If given, count only occurances of that column. The default is None.
- Returns