def main():
data = load_data()
freq = calc_word_freq(data)
freq = sorted(freq.values(), reverse=True)
plt.loglog(range(1, len(freq) + 1), freq)
plt.show()
return 0
def main():
data = load_data()
freq = calc_word_freq(data)
freq = sorted(freq.values(), reverse=True)
plt.loglog(range(1, len(freq)+1), freq)
plt.show()
return 0
def main():
data = load_data()
freq = calc_word_freq(data)
plt.hist(freq.values(), bins=100)
plt.show()
# 頻度50以下の単語を除いてみる
plt.hist(filter(lambda t: t > 50, freq.values()), bins=100)
plt.show()
return 0
def main():
data = load_data()
freq = calc_word_freq(data)
plt.hist(freq.values(), bins=100)
plt.show()
# 頻度50以下の単語を除いてみる
plt.hist(filter(lambda t: t>50, freq.values()), bins=100)
plt.show()
return 0
def main():
data = load_data()
freq = calc_word_freq(data)
# 上位10単語の取り出し
words = sorted(freq.items(), key=lambda t: t[1], reverse=True)[:10]
keys, values = zip(*words) # キーと頻度に分ける
width = 0.5
plt.bar([i + width / 2.0 for i in range(10)], values, width)
plt.xticks([i + width for i in range(10)], keys)
plt.show()
return 0
def main():
data = load_data()
freq = calc_word_freq(data)
# 上位10単語の取り出し
words = sorted(freq.items(), key=lambda t:t[1], reverse=True)[:10]
keys, values = zip(*words) # キーと頻度に分ける
width = 0.5
plt.bar([i + width/2.0 for i in range(10)],
values, width)
plt.xticks([i + width for i in range(10)], keys)
plt.show()
return 0
