forked from saret/DHGeography
33 lines
951 B
Python
33 lines
951 B
Python
import pandas as pd
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import plotly.express as px
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import plotly.graph_objects as go
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# Read the CSV file into a Pandas DataFrame
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file_path = "texts_by_period_and_location_saparated_by_periods_in_columns.csv"
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df = pd.read_csv(file_path)
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# Define the columns to summarize
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columns_to_summarize = ["ancient", "old", "middle", "new", "late"]
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# Group the data by the "place" column and calculate sums within each group
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grouped = df.groupby("place")[columns_to_summarize].sum().reset_index()
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# Create a bar chart using Plotly
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fig = go.Figure()
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# Add a bar trace for each category
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for col in columns_to_summarize:
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fig.add_trace(go.Bar(x=grouped["place"], y=grouped[col], name=col))
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# Customize the layout
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fig.update_layout(
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title="Summary of Categories by Place with Filtering",
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xaxis_title="Place",
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yaxis_title="Total Count",
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xaxis=dict(categoryorder='total descending'),
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barmode='group'
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)
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# Show the interactive graph
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fig.show()
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