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import pandas as pd
%matplotlib inline
from ast import literal_eval
import numpy as np
import re
from matplotlib import pyplot as plt
plt.rcParams["figure.figsize"] = [16, 6]
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df = pd.read_csv('e0a/log.txt')
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def getDate(filename):
"""
Extract dates from filenames.
"""
m = re.search('_(\d{4})_', filename)
if m is not None:
return int(m.group(1))
else:
return None
df['Date'] = df['Text B'].apply(getDate)
df['Decade'] = df['Date'] - (df['Date'] % 10)
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df.head()
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df['Date'].hist()
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textALength = df['Text A Length'][0]
textALength
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decades = np.arange(1930, 2020, 10)
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# Make a dictionary of decades.
# Values are a list of locations.
decadeDict = {}
for i, row in df.iterrows():
decade = row['Decade']
locations = literal_eval(row['Locations in A'])
if decade not in decadeDict:
decadeDict[decade] = locations
else:
decadeDict[decade] += locations
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# Grab the beginnings of quotes.
decadeStarts = {decade: [item[0] for item in loc] for decade, loc in decadeDict.items()}
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decadesBinned = {decade:
np.histogram(locations, bins=50, range=(0, textALength))[0]
for decade, locations in decadeStarts.items() if decade in decades}
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decadesDF = pd.DataFrame(decadesBinned).T
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decadesDF
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ylabels = [str(int(decade)) for decade in decadesDF.index] + ['2020']
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plt.pcolor(decadesDF)
plt.yticks(np.arange(len(decadesDF.index)+1), ylabels)
plt.gca().invert_yaxis()
plt.ylabel('Decade')
plt.xlabel('Quotes Per Novel Segment')
plt.title("Number of Critical Quotations from George Eliot's Middlemarch, By Decade")
#plt.xticks(np.arange(len(decadesDF.columns)), decadesDF.columns)
plt.show()
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decadesDF.sum().plot(kind='bar')
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