forked from saret/DHGeography
36 lines
1.2 KiB
Python
36 lines
1.2 KiB
Python
import pandas as pd
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import matplotlib.pyplot as plt
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import numpy as np
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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 list of colors for the inner divisions
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colors = ["#1f77b4", "#ff7f0e", "#2ca02c", "#d62728", "#9467bd"]
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# Create the figure and axis for the bar chart
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fig, ax = plt.subplots()
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# Create bars for each place with inner divisions
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bottom = np.zeros(len(grouped))
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for i, col in enumerate(columns_to_summarize):
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ax.bar(grouped["place"], grouped[col], 0.6, bottom=bottom, color=colors[i], label=col)
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bottom += grouped[col]
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# Customize the plot
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ax.set_ylabel("Total Count")
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ax.set_title("Summary of Categories by Place with Inner Divisions")
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ax.set_xticks(np.arange(len(grouped["place"])))
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ax.set_xticklabels(grouped["place"], rotation=45, ha="right")
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ax.legend(loc='upper right')
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# Display the plot
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plt.show()
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