如何下载谷歌ngram页面数据？

[chengjun]

第一步，查询词语

https://books.google.com/ngrams/graph?content=Albert+Einstein%2CSherlock+Holmes%2CFrankenstein&year_start=1800&year_end=2019&corpus=26&smoothing=0&direct_url=t1%3B%2CAlbert%20Einstein%3B%2Cc0%3B.t1%3B%2CSherlock%20Holmes%3B%2Cc0%3B.t1%3B%2CFrankenstein%3B%2Cc0#t1%3B%2CAlbert%20Einstein%3B%2Cc1%3B.t1%3B%2CSherlock%20Holmes%3B%2Cc1%3B.t1%3B%2CFrankenstein%3B%2Cc0

第二步，查看网页源代码

view-source:https://books.google.com/ngrams/graph?content=Albert+Einstein%2CSherlock+Holmes%2CFrankenstein&year_start=1800&year_end=2019&corpus=26&smoothing=0&direct_url=t1%3B%2CAlbert%20Einstein%3B%2Cc0%3B.t1%3B%2CSherlock%20Holmes%3B%2Cc0%3B.t1%3B%2CFrankenstein%3B%2Cc0#t1%3B%2CAlbert%20Einstein%3B%2Cc0%3B.t1%3B%2CSherlock%20Holmes%3B%2Cc1%3B.t1%3B%2CFrankenstein%3B%2Cc0

第三部，使用 timeseries搜索即可找到数据，将包含timeseries的这一行复制下来即可

ngramsdata = [{"ngram": "Albert Einstein", "parent": "", "type": "NGRAM", "timeseries": [0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 6.354231807392807e-09, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 7.515418509740357e-09, 0.0, 0.0, 0.0, 0.0, 0.0, 7.061168982858135e-09, 0.0, 0.0, 3.4191243170056396e-09, 0.0, 0.0, 2.2431805302147723e-09, 0.0, 0.0, 0.0, 0.0, 0.0, 5.619823717495365e-09, 4.472740400274233e-09, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 2.1717909692853254e-09, 1.0143155204644927e-09, 6.447877232140797e-10, 0.0, 7.012160851971316e-10, 0.0, 0.0, 0.0, 4.0653774791010733e-10, 0.0, 0.0, 1.8599565221322223e-09, 0.0, 0.0, 5.902292543602528e-10, 2.626655870585637e-08, 0.0, 4.783005991271239e-09, 0.0, 2.2535111554589093e-09, 0.0, 2.7315261164062576e-10, 0.0, 2.7290127491141902e-08, 1.8713981475571018e-09, 9.963826208547744e-09, 0.0, 1.2088865464221499e-09, 9.301427961183606e-10, 1.7524461881635034e-08, 1.2613954325502164e-09, 2.8067363988526495e-09, 1.2835523754972655e-09, 0.0, 1.9322113353759107e-10, 4.223416727455742e-09, 1.2885598144052324e-09, 7.008972957578408e-09, 2.43883091499697e-09, 4.0419796398794006e-09, 4.601610203991413e-09, 1.3456737946171415e-09, 4.603338266129242e-10, 4.4081394090511594e-10, 2.816973043717752e-10, 3.8695158188772893e-10, 9.017939284206022e-09, 7.194682627442717e-10, 4.842662382209539e-10, 3.724408337291152e-09, 1.1394521992613704e-09, 3.2046933995388827e-09, 5.401033398300115e-09, 3.1609873052396154e-10, 1.013002792760176e-09, 1.4437663287125702e-09, 9.738764239486386e-10, 2.7367080823736956e-10, 2.1976798159073496e-09, 4.027834510367256e-09, 1.950475336798263e-09, 6.228209059599976e-09, 3.516303470618709e-09, 2.332998239040762e-09, 6.890880754895079e-09, 1.5020120258668612e-08, 7.488149122991672e-08, 9.687033752925345e-08, 5.669327407531455e-08, 6.845207423111788e-08, 4.706938483423073e-08, 4.942612719105455e-08, 4.9794294909588643e-08, 4.967654732013216e-08, 5.0152468844544273e-08, 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8.729298315302003e-07, 8.7161703277161e-07, 9.065900599125598e-07, 7.772651429149846e-07, 7.742853540548822e-07, 8.410036684836086e-07]}, {"ngram": "Sherlock Holmes", "parent": "", "type": "NGRAM", "timeseries": [1.892719225793371e-08, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 1.734112076157146e-09, 0.0, 1.3988989966406962e-09, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 1.1959677692630066e-09, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 3.295212325227226e-09, 1.2757743750313466e-09, 0.0, 2.849270153149064e-09, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 5.071585928995148e-10, 0.0, 4.683186616283308e-10, 0.0, 8.775266069349641e-10, 0.0, 4.4663234222142023e-10, 0.0, 2.83602763495594e-09, 3.656194513812494e-10, 1.4375275414479916e-09, 2.221397288337812e-09, 0.0, 6.762103654800455e-10, 3.2239386160703987e-10, 3.372455370520555e-10, 3.506080425985658e-10, 1.326633691789425e-09, 3.211248766898933e-10, 7.308181171339356e-09, 1.6261509916404293e-09, 1.222131285061323e-09, 0.0, 7.439825977506587e-10, 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for i in range(len(ngramsdata)):
    print(ngramsdata[i]['ngram'])
    print(ngramsdata[i]['timeseries'][:10])

Albert Einstein
[0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0]
Sherlock Holmes
[1.892719225793371e-08, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 1.734112076157146e-09, 0.0]
Frankenstein
[8.730623335395649e-08, 1.6202386987629325e-08, 1.6821548598500158e-08, 4.3224709145306406e-08, 6.175727662594e-08, 2.1272212435974325e-08, 4.9139994295899214e-09, 1.1745486006020656e-07, 4.5443563578828616e-08, 9.04925379074939e-09]

year = range(1800, 2019+1)

for i in range(len(ngramsdata)):
    plt.plot(year, ngramsdata[i]['timeseries'], label = ngramsdata[i]['ngram'])
plt.xlabel('Year', fontsize = 16)
plt.ylabel('Relative Frequency', fontsize = 16)
plt.ylim([0, 0.00000220])
plt.legend();