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How to use the retentioneering.visualization.funnel.funnel_chart function in retentioneering

To help you get started, we’ve selected a few retentioneering examples, based on popular ways it is used in public projects.

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github retentioneering / retentioneering-tools / retentioneering / core / utils.py View on Github external
Return type
        --------
        Plotly
        """
        self._init_cols(locals())
        if user_based:
            counts = self.filter_cluster(
                cluster, index_col=self._index_col()
            ).groupby(self._event_col())[self._index_col()].nunique().loc[funnel_events]
        else:
            counts = self.filter_cluster(
                cluster, index_col=index_col
            ).groupby(self._event_col())[self._event_time_col()].count().loc[funnel_events]
        counts = counts.fillna(0)
        return funnel.funnel_chart(counts.astype(int).tolist(),
                                   funnel_events,
                                   'Funnel for cluster {}'.format(cluster),
                                   interactive=interactive)

retentioneering

Retentioneering is a Python library that makes analyzing clickstreams, user paths (trajectories), and event logs much easier, and yields much broader and deeper insights than funnel analysis. You can use Retentioneering to explore user behavior, segment users, and form hypotheses about what drives users to desirable actions or to churning away from a product.

GitHub
Retentioneering Software Non-…
Latest version published 1 year ago

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