70 lines
1.9 KiB
Python
70 lines
1.9 KiB
Python
import statistics
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import requests
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import json
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import matplotlib.pyplot as plt
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import numpy
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import os
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import pandas
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pandas.options.display.float_format = '{:.10f}'.format
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words = input('Please enter a list of words. Separate each word with a comma (:\n')
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print()
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startYear = 1800
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endYear = 2019
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years = range(startYear, endYear + 1)
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response = requests.get('https://books.google.com/ngrams/json?content=%s&year_start=%s&year_end=%s&corpus=26&smoothing=3' % (words, startYear, endYear))
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data = json.loads(response.content)
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frames = []
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for x in data:
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frame = {}
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points = x['timeseries']
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frame['word'] = x['ngram']
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frame['stdev'] = numpy.std(points)
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frame['mean'] = numpy.mean(points)
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frame['median'] = numpy.median(points)
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frame['mode'] = statistics.mode(points)
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frame['range'] = max(points) - min(points)
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frame['q1'] = numpy.percentile(points, 25)
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frame['q3'] = numpy.percentile(points, 75)
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frame['iqr'] = frame['q3'] - frame['q1']
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frames.append(frame)
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plt.plot(years, points, label=frame['word'])
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df = pandas.DataFrame(frames)
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print(df)
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# Summary Statistics
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for frame in frames:
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print()
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if frame['stdev'] == max([ f['stdev'] for f in frames ]):
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print('%s has the highest standard deviation!' % (frame['word']))
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elif frame['stdev'] == min([ f['stdev'] for f in frames ]):
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print('%s has the lowest standard deviation!' % (frame['word']))
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# Save CSV
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dirName = os.path.dirname(os.path.realpath(__file__))
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wordList = ', '.join([f['word'] for f in frames])
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while True:
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toSave = input('Would you like to save this data frame in a CSV? (y/n)')
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if toSave == 'y':
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df.to_csv('%s/%s.csv' % (dirName, wordList))
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break
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if toSave == 'n':
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break
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# Save Graph
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while True:
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toSave = input('Would you like to save a graph of the data? (y/n)').lower()
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if toSave == 'y':
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plt.ticklabel_format(style='plain')
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plt.legend()
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plt.savefig('%s/%s.png' % (dirName, wordList), dpi=100)
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exit()
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elif toSave == 'n':
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exit()
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