niimpy.exploration.eda.categorical module

Created on Thu Nov 18 14:49:22 2021

@author: arsii

niimpy.exploration.eda.categorical.categorize_answers(df, question)[source]

Extract a question answered and count different answers.

Parameters:
dfPandas Dataframe

Dataframe containing questionnaire data

questionstr

dataframe column sontaining question id

answer_columnstr

dataframe column containing the answer

Returns:
category_counts: Pandas Dataframe

Dataframe containing the category counts of answers filtered by the question

niimpy.exploration.eda.categorical.get_xticks_(ser)[source]

Helper function for plot_categories function. Convert series index into xtick values and text.

Parameters:
serPandas series

Series containing the categorized counts

niimpy.exploration.eda.categorical.plot_categories(df, title=None, xlabel=None, ylabel=None, width=900, height=900)[source]

Create a barplot of categorical data

Parameters:
dfPandas Dataframe

Dataframe containing categorized data

titlestr

Plot title

xlabelstr

Plot xlabel

ylabelstr

Plot ylabel

widthinteger

Plot width

heightinteger

Plot height

Returns:
fig: plotly Figure

A barplot of the input data

niimpy.exploration.eda.categorical.plot_grouped_categories(df, group, title=None, xlabel=None, ylabel=None, width=900, height=900)[source]

Plot summary barplot for questionnaire data.

Parameters:
df: Pandas DataFrameGroupBy

A grouped dataframe containing categorical data

group: str

Column used to describe group

titlestr

Plot title

xlabelstr

Plot xlabel

ylabelstr

Plot ylabel

widthinteger

Plot width

heightinteger

Plot height

Returns:
fig: plotly Figure

Figure containing barplots of the data in each group

niimpy.exploration.eda.categorical.question_by_group(df, question, group='group')[source]

Plot summary barplot for questionnaire data.

Parameters:
dfPandas Dataframe

Dataframe containing questionnaire data

questionstr

question id

answer_columnstr

answer_column containing the answer

groupstr

group by this column

Returns:
dfPandas DataFrameGroupBy

Dataframe a single answers column filtered by the question parameter and grouped by the group parameter

niimpy.exploration.eda.categorical.questionnaire_grouped_summary(df, question, group='group', title=None, xlabel=None, ylabel=None, width=900, height=900)[source]

Create a barplot of categorical data

Parameters:
dfPandas Dataframe

Dataframe containing questionnaire data

questionstr

question id

titlestr

Plot title

xlabelstr

Plot xlabel

ylabelstr

Plot ylabel

userBool or str

If str, plot single user data If False, plot group level data

groupstr

group by this column

Returns:
fig: plotly Figure

A barplot of the input data

niimpy.exploration.eda.categorical.questionnaire_summary(df, question, title=None, xlabel=None, ylabel=None, user=None, width=900, height=900)[source]

Plot summary barplot for questionnaire data.

Parameters:
dfPandas Dataframe

Dataframe containing questionnaire data

questionstr

question id

titlestr

Plot title

xlabelstr

Plot xlabel

ylabelstr

Plot ylabel

userBool or str

If str, plot single user data If False, plot group level data

Returns:
fig: plotly Figure

A barplot summary of the questionnaire