# -*- coding: utf-8 -*-
"""
Created on Mon Nov 8 14:42:18 2021
@author: arsii
"""
import pandas as pd
import plotly.express as px
[docs]def get_counts(df,aggregation):
"""Calculate datapoint counts by group or by user
Parameters
----------
df : Pandas DataFrame
aggregation : str
Returns
-------
n_events : Pandas DataFrame
"""
assert isinstance(df,pd.DataFrame), "df is not a pandas dataframe."
assert isinstance(aggregation,str), "aggregation is not a string"
if aggregation == 'group':
n_events = df[['group', 'user']].groupby(['group']).size().to_frame()
n_events.columns = ['values']
n_events = n_events.reset_index()
elif aggregation == 'user':
n_events = df[['user']].groupby(['user']).size().to_frame()
n_events.columns = ['values']
n_events = n_events.reset_index()
return n_events
[docs]def calculate_bins(df,binning):
"""Calculate time index based bins for each observation in the dataframe.
Parameters
----------
df : Pandas DataFrame
binning : str
to_string : bool
Returns
-------
bins : pandas period index
"""
assert isinstance(df,pd.DataFrame), "df is not a pandas dataframe."
assert isinstance(binning,str), "binning is not a string"
#assert isinstance(to_string,bool), "to_string is not a bool"
bins = df.index.to_period(binning)
bins = bins.to_series().astype(str)
return bins
[docs]def boxplot_(df, fig_title, points = 'outliers', y = 'values', xlabel="Group", ylabel="Count",binning=False):
"""Plot a boxplot
Parameters
----------
df : Pandas Dataframe
Dataframe containing the data
fig_title : str
Plot title
points : str
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
xlabel : str
Plot xlabel
ylabel : str
Plot ylabel
Returns
-------
"""
assert isinstance(df,pd.DataFrame), "df is not a pandas dataframe."
assert isinstance(points,str), "points is not a string"
assert isinstance(y,str), "y is not a string"
assert isinstance(fig_title,str), "Title is not a string."
assert isinstance(xlabel,str), "Xlabel is not a string."
assert isinstance(ylabel,str), "Ylabel is not a string."
assert ((isinstance(binning,str)) or (binning,bool)), "binning."
#TODO! check if this is necessary!
#df[y] = df[y].astype(np.float64)
if binning is not False:
df['bin'] = calculate_bins(df,binning).values
fig = px.box(df,
x = "bin",
y = y,
color = "group",
)
else:
fig = px.box(df,
x = "group",
y = y,
color = "group",
points = points)
fig.update_traces(quartilemethod='inclusive') # or "inclusive", or "linear" by default
fig.update_layout(title = fig_title,
xaxis_title = xlabel,
yaxis_title = ylabel,
autotypenumbers='convert types')
return fig
[docs]def barplot_(df, fig_title, xlabel, ylabel):
"""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
----------
df : Pandas Dataframe
Dataframe containing the data
fig_title : str
Plot title
xlabel : str
Plot xlabel
ylabel : str
Plot ylabel
Returns
-------
"""
assert isinstance(df,pd.DataFrame), "df is not a pandas dataframe."
assert isinstance(fig_title,str), "Title is not a string."
assert isinstance(xlabel,str), "Xlabel is not a string."
assert isinstance(ylabel,str), "Ylabel is not a string."
fig = px.bar(df,
x = "user",
y = "values",
color = "user")
fig.update_layout(title = fig_title,
xaxis_title = xlabel,
yaxis_title = ylabel)
return fig
[docs]def countplot(df, fig_title, plot_type = 'count', points = 'outliers',aggregation = 'group', user = None, column=None, binning=False):
"""Create boxplot comparing groups or individual users.
Parameters
----------
df : pandas DataFrame
A DataFrame to be visuliazed
fig_title : str
The plot title.
plot_type : str
If 'count', plot observation count per group (boxplot) or by user (barplot)
If 'value', plot observation values per group (boxplot)
The default is 'count'
aggregation : str
If 'group', plot group level summary
If 'user', plot user level summary
The default is 'group'
user : str
if given ...
The default is None
column : str, optional
if None, count number of rows. If given, count only occurances of that column.
The default is None.
Returns
-------
"""
assert isinstance(df,pd.DataFrame), "df is not a pandas dataframe."
assert isinstance(fig_title,str), "Title is not a string."
assert isinstance(plot_type, str), "plot_type is not a string."
assert isinstance(points,str), "points is not a string"
assert isinstance(aggregation,str), "aggregation is not a string"
assert ((isinstance(user,str)) or (user is None)), "user is not a string or None type."
assert ((isinstance(column,str)) or (column is None)), "column in not a string or None type."
# Plot counts
if plot_type == 'count':
if aggregation == 'group':
n_events = get_counts(df,aggregation)
fig = boxplot_(n_events,
fig_title,
points,
y = 'values',
xlabel="Group",
ylabel="Count",
binning=binning
)
elif aggregation == 'user':
n_events = get_counts(df,aggregation)
fig = barplot_(n_events,
fig_title,
xlabel="User",
ylabel="Count")
else:
pass
# Plot values
elif plot_type == 'value':
if aggregation == 'group':
fig = boxplot_(df,
fig_title,
points,
y=column,
xlabel="Group",
ylabel="Value",
binning=binning
)
else:
pass
return fig