Add word popularity checker

python/data science/ngrams/popularity/popularity.py

@@ -0,0 +1,42 @@
+import requests
+import json
+import matplotlib.pyplot as graph
+import numpy
+import statistics
+import os
+import pandas
+
+pandas.options.display.float_format = '{:.10f}'.format
+
+word = input('Please enter a word to research!\n')
+print()
+startYear = 1800
+endYear = 2019
+years = range(startYear, endYear + 1)
+
+response = requests.get('https://books.google.com/ngrams/json?content=%s&year_start=%s&year_end=%s&corpus=26&smoothing=3' % (word, startYear, endYear))
+data = json.loads(response.content)[0]
+
+frame = {}
+points = data['timeseries']
+
+frame['word'] = data['ngram']
+frame['stdev'] = numpy.std(points)
+frame['mean'] = numpy.mean(points)
+frame['median'] = numpy.median(points)
+frame['mode'] = statistics.mode(points)
+frame['range'] = max(points) - min(points)
+frame['q1'] = numpy.percentile(points, 25)
+frame['q3'] = numpy.percentile(points, 75)
+frame['iqr'] = frame['q3'] - frame['q1']
+
+df = pandas.DataFrame([frame])
+print(df)
+
+m, b = numpy.polyfit(years, points, 1)
+
+graph.plot(years, points)
+graph.plot(years, m * years + b)
+graph.title(frame['word'])
+graph.ticklabel_format(style='plain')
+graph.savefig('%s/%s.png' % (os.path.dirname(os.path.realpath(__file__)), word), dpi=100)

readme.md

@@ -12,7 +12,9 @@
 - [Data Science](python/data%20science)
   - [Fake Jobs Scraper](python/data%20science/fakejobs.py)
   - [Country Population vs Active Facebook Users in the Country](python/data%20science/facebook.py)
-  - [ngram comparison](python/data%20science/ngrams%20comparison/ngram%20comparison.py)
+  - [ngrams](python/data%20science/ngrams)
+    - [Comparison](python/data%20science/ngrams/comparison/comparison.py)
+    - [Popularity](python/data%20science/ngrams/popularity/popularity.py)
 - [Calculators](python/calculators)
   - [Binomial Distribution](python/calculators/binomial%20distribution.py)
   - [Pearson's Product-Moment Correlation Coefficient](python/calculators/pmcc.py)