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Evidence Gap Maps(egm) are useful for visualizing research gaps. This library (extension of theBubbly package) provides interactive and animated charts usingPlotly, useful for plotting reasearch papers. The animated bubble charts can accommodate multiple variables viz. X-axis, Y-axis, time, bubbles (the research artifacts of title , abstract and doi) their size (similarity to research question) and their color in a compact and captivating way. Evidence Gap Maps (egm) python package is easy to use with plenty of customization, and is designed to work withplotly's offline mode useful in Jupyter Notebooks, Google Colab and Kaggle kernels.

egm package can also be useful in making a plot where two catagorical variable are to be plotted aganst each other as bins.

• Python 3.x
• numpy
• pandas
• plotly

pip install egm

There are two modes supported. Time can be included in both modes for a dynamic year wise plot.

1. Mode Random

The random mode is more display friendly and the plot in a bin is scattered evenly.

figure =evidencegapmap(dataset=pd, x_column='x', y_column='y',bubble_column='title_column',bubble_text='bubbletext_column', bubble_link='bubblelink_column', size_column='size_column', color_column='color_column',xbin_list=, ybin_list = ,xbin_size=100, ybin_size = 100, x_title="X Axis Title", y_title="Y Axis Title", title='Evidence Gap Map for XYZ',scale_bubble=4, marker_opacity=0.8,height=900, width=1200)

2. NLP Mode

For the NLP mode, x and y coordinates are provided arrays and are transformed and plotted in the bin. The mode is useful for displaying the similarity and disimilarity of research papers

figure =evidencegapmap(dataset=pd, x_column='x', y_column='y',xy_column='xy_column',bubble_column='title_column',bubble_text='bubbletext_column', bubble_link='bubblelink_column', time_column='publish_year', size_column='size_column', color_column='color_column',xbin_list=, ybin_list = ,xbin_size=100, ybin_size = 100, x_title="X Axis Title", y_title="Y Axis Title", title='Evidence Gap Map for XYZ',scale_bubble=4, marker_opacity=0.8,height=900, width=1200)

Refer to thiscollab notebook for a basic working example withsample data

View an end to end working examplehere