FigureBuilder¶
whatstk provides this object to ease the generation of insightfull plots from your chat. FigureBuilder
contains several methods to generate different plots. It assigns a unique color to each user,
so that a user can be easily identified in all plots.
To insantiate it, you just need to provide the chat (as pandas.DataFrame or BaseChat
-API-compliant object).
- class whatstk.FigureBuilder(df: DataFrame | None = None, chat: BaseChat | None = None)[source]¶
Bases:
object
Generate a variety of figures from your loaded chat.
Integrates feature extraction and visualization logic to automate data plots.
Note: Either
df
orchat
must be provided.- Parameters:
df (pandas.DataFrame, optional) – Chat data. Atribute df of a chat loaded using Chat. If a value is given,
chat
is ignored.chat (Chat, optional) – Chat data. Object obtained when chat loaded using Chat. Required if
df
is None.
Attributes:
Get mapping between user and color.
Get list with users available in given chat.
Methods:
Plot number of user interventions over time.
user_message_responses_flow
([title])Get the flow of message responses.
user_message_responses_heatmap
([norm, title])Get the response matrix heatmap.
user_msg_length_boxplot
([title, xlabel])Generate figure with boxplots of each user's message length.
- property user_color_mapping: Dict[str, str]¶
Get mapping between user and color.
Each user is assigned a color automatically, so that this color is preserved for that user in all to-be-generated plots.
- Returns:
dict – Mapping from username to color (rgb).
- user_interventions_count_linechart(date_mode: str = 'date', msg_length: bool = False, cumulative: bool = False, all_users: bool = False, title: str = 'User interventions count', xlabel: str = 'Date/Time') Figure [source]¶
Plot number of user interventions over time.
- Parameters:
date_mode (str, optional) –
Choose mode to group interventions by. Defaults to
'date'
. Available modes are:'date'
: Grouped by particular date (year, month and day).'hour'
: Grouped by hours.'month'
: Grouped by months.'weekday'
: Grouped by weekday (i.e. monday, tuesday, …, sunday).'hourweekday'
: Grouped by weekday and hour.
msg_length (bool, optional) – Set to True to count the number of characters instead of number of messages sent.
cumulative (bool, optional) – Set to True to obtain commulative counts.
all_users (bool, optional) – Obtain number of interventions of all users combined. Defaults to False.
title (str, optional) – Title for plot. Defaults to “User interventions count”.
xlabel (str, optional) – x-axis label title. Defaults to “Date/Time”.
- Returns:
plotly.graph_objs.Figure – Plotly Figure.
See also
Example
>>> from whatstk import WhatsAppChat >>> from whatstk.graph import plot, FigureBuilder >>> from whatstk.data import whatsapp_urls >>> chat = WhatsAppChat.from_source(filepath=whatsapp_urls.LOREM) >>> fig = FigureBuilder(chat=chat).user_interventions_count_linechart(cumulative=True) >>> plot(fig)
- user_message_responses_flow(title: str = 'Message flow') Figure [source]¶
Get the flow of message responses.
A response from user X to user Y happens if user X sends a message right after a message from user Y.
Uses a Sankey diagram.
- Parameters:
title (str, optional) – Title for plot. Defaults to “Message flow”.
- Returns:
plotly.graph_objs.Figure – Plotly Figure.
See also
Example
>>> from whatstk import WhatsAppChat >>> from whatstk.graph import plot, FigureBuilder >>> from whatstk.data import whatsapp_urls >>> chat = WhatsAppChat.from_source(filepath=whatsapp_urls.LOREM) >>> fig = FigureBuilder(chat=chat).user_message_responses_flow() >>> plot(fig)
- user_message_responses_heatmap(norm: str = 'absolute', title: str = 'Response matrix') Figure [source]¶
Get the response matrix heatmap.
A response from user X to user Y happens if user X sends a message right after a message from user Y.
- Parameters:
norm (str, optional) –
Specifies the type of normalization used for reponse count. Can be:
'absolute'
: Absolute count of messages.'joint'
: Normalized by total number of messages sent by all users.'sender'
: Normalized per sender by total number of messages sent by user.'receiver'
: Normalized per receiver by total number of messages sent by user.
title (str, optional) – Title for plot. Defaults to “Response matrix”.
- Returns:
plotly.graph_objs.Figure – Plotly Figure.
See also
Example
>>> from whatstk import WhatsAppChat >>> from whatstk.graph import plot, FigureBuilder >>> from whatstk.data import whatsapp_urls >>> chat = WhatsAppChat.from_source(filepath=whatsapp_urls.LOREM) >>> fig = FigureBuilder(chat=chat).user_message_responses_heatmap() >>> plot(fig)
- user_msg_length_boxplot(title: str = 'User message length', xlabel: str = 'User') Figure [source]¶
Generate figure with boxplots of each user’s message length.
- Parameters:
title (str, optional) – Title for plot. Defaults to “User message length”.
xlabel (str, optional) – x-axis label title. Defaults to “User”.
- Returns:
dict – Dictionary with data and layout. Plotly compatible.
See also
Example
>>> from whatstk import WhatsAppChat >>> from whatstk.graph import plot, FigureBuilder >>> from whatstk.data import whatsapp_urls >>> chat = WhatsAppChat.from_source(filepath=whatsapp_urls.LOREM) >>> fig = FigureBuilder(chat=chat).user_msg_length_boxplot() >>> plot(fig)