page124

# coding=utf-8
import pandas as pd
from matplotlib import pyplot as plt
file_path = "./IMDB-Movie-Data.csv"
df = pd.read_csv(file_path)
# print(df.head(1))
# print(df.info())
#rating,runtime分布情况
#选择图形，直方图
#准备数据
runtime_data = df["Rating"].values
max_runtime = runtime_data.max()
min_runtime = runtime_data.min()
#计算组数
print(max_runtime-min_runtime)
num_bin = (max_runtime-min_runtime)//0.5
#设置图形的大小
plt.figure(figsize=(20,8),dpi=80)
plt.hist(runtime_data,num_bin)
_x = [min_runtime]
i = min_runtime
while i<=max_runtime+0.5:
    i = i+0.5
    _x.append(i)
plt.xticks(_x)
plt.show()

import numpy as np
from matplotlib import pyplot as plt
runtime_data = np.array([8.1, 7.0, 7.3, 7.2, 6.2, 6.1, 8.3, 6.4, 7.1, 7.0, 7.5, 7.8, 7.9, 7.7, 6.4, 6.6, 8.2, 6.7, 8.1, 8.0, 6.7, 7.9, 6.7, 6.5, 5.3, 6.8, 8.3, 4.7, 6.2, 5.9, 6.3, 7.5, 7.1, 8.0, 5.6, 7.9, 8.6, 7.6, 6.9, 7.1, 6.3, 7.5, 2.7, 7.2, 6.3, 6.7, 7.3, 5.6, 7.1, 3.7, 8.1, 5.8, 5.6, 7.2, 9.0, 7.3, 7.2, 7.4, 7.0, 7.5, 6.7, 6.8, 6.5, 4.1, 8.5, 7.7, 7.4, 8.1, 7.5, 7.2, 5.9, 7.1, 7.5, 6.8, 8.1, 7.1, 8.1, 8.3, 7.3, 5.3, 8.8, 7.9, 8.2, 8.1, 7.2, 7.0, 6.4, 7.8, 7.8, 7.4, 8.1, 7.0, 8.1, 7.1, 7.4, 7.4, 8.6, 5.8, 6.3, 8.5, 7.0, 7.0, 8.0, 7.9, 7.3, 7.7, 5.4, 6.3, 5.8, 7.7, 6.3, 8.1, 6.1, 7.7, 8.1, 5.8, 6.2, 8.8, 7.2, 7.4, 6.7, 6.7, 6.0, 7.4, 8.5, 7.5, 5.7, 6.6, 6.4, 8.0, 7.3, 6.0, 6.4, 8.5, 7.1, 7.3, 8.1, 7.3, 8.1, 7.1, 8.0, 6.2, 7.8, 8.2, 8.4, 8.1, 7.4, 7.6, 7.6, 6.2, 6.4, 7.2, 5.8, 7.6, 8.1, 4.7, 7.0, 7.4, 7.5, 7.9, 6.0, 7.0, 8.0, 6.1, 8.0, 5.2, 6.5, 7.3, 7.3, 6.8, 7.9, 7.9, 5.2, 8.0, 7.5, 6.5, 7.6, 7.0, 7.4, 7.3, 6.7, 6.8, 7.0, 5.9, 8.0, 6.0, 6.3, 6.6, 7.8, 6.3, 7.2, 5.6, 8.1, 5.8, 8.2, 6.9, 6.3, 8.1, 8.1, 6.3, 7.9, 6.5, 7.3, 7.9, 5.7, 7.8, 7.5, 7.5, 6.8, 6.7, 6.1, 5.3, 7.1, 5.8, 7.0, 5.5, 7.8, 5.7, 6.1, 7.7, 6.7, 7.1, 6.9, 7.8, 7.0, 7.0, 7.1, 6.4, 7.0, 4.8, 8.2, 5.2, 7.8, 7.4, 6.1, 8.0, 6.8, 3.9, 8.1, 5.9, 7.6, 8.2, 5.8, 6.5, 5.9, 7.6, 7.9, 7.4, 7.1, 8.6, 4.9, 7.3, 7.9, 6.7, 7.5, 7.8, 5.8, 7.6, 6.4, 7.1, 7.8, 8.0, 6.2, 7.0, 6.0, 4.9, 6.0, 7.5, 6.7, 3.7, 7.8, 7.9, 7.2, 8.0, 6.8, 7.0, 7.1, 7.7, 7.0, 7.2, 7.3, 7.6, 7.1, 7.0, 6.0, 6.1, 5.8, 5.3, 5.8, 6.1, 7.5, 7.2, 5.7, 7.7, 7.1, 6.6, 5.7, 6.8, 7.1, 8.1, 7.2, 7.5, 7.0, 5.5, 6.4, 6.7, 6.2, 5.5, 6.0, 6.1, 7.7, 7.8, 6.8, 7.4, 7.5, 7.0, 5.2, 5.3, 6.2, 7.3, 6.5, 6.4, 7.3, 6.7, 7.7, 6.0, 6.0, 7.4, 7.0, 5.4, 6.9, 7.3, 8.0, 7.4, 8.1, 6.1, 7.8, 5.9, 7.8, 6.5, 6.6, 7.4, 6.4, 6.8, 6.2, 5.8, 7.7, 7.3, 5.1, 7.7, 7.3, 6.6, 7.1, 6.7, 6.3, 5.5, 7.4, 7.7, 6.6, 7.8, 6.9, 5.7, 7.8, 7.7, 6.3, 8.0, 5.5, 6.9, 7.0, 5.7, 6.0, 6.8, 6.3, 6.7, 6.9, 5.7, 6.9, 7.6, 7.1, 6.1, 7.6, 7.4, 6.6, 7.6, 7.8, 7.1, 5.6, 6.7, 6.7, 6.6, 6.3, 5.8, 7.2, 5.0, 5.4, 7.2, 6.8, 5.5, 6.0, 6.1, 6.4, 3.9, 7.1, 7.7, 6.7, 6.7, 7.4, 7.8, 6.6, 6.1, 7.8, 6.5, 7.3, 7.2, 5.6, 5.4, 6.9, 7.8, 7.7, 7.2, 6.8, 5.7, 5.8, 6.2, 5.9, 7.8, 6.5, 8.1, 5.2, 6.0, 8.4, 4.7, 7.0, 7.4, 6.4, 7.1, 7.1, 7.6, 6.6, 5.6, 6.3, 7.5, 7.7, 7.4, 6.0, 6.6, 7.1, 7.9, 7.8, 5.9, 7.0, 7.0, 6.8, 6.5, 6.1, 8.3, 6.7, 6.0, 6.4, 7.3, 7.6, 6.0, 6.6, 7.5, 6.3, 7.5, 6.4, 6.9, 8.0, 6.7, 7.8, 6.4, 5.8, 7.5, 7.7, 7.4, 8.5, 5.7, 8.3, 6.7, 7.2, 6.5, 6.3, 7.7, 6.3, 7.8, 6.7, 6.7, 6.6, 8.0, 6.5, 6.9, 7.0, 5.3, 6.3, 7.2, 6.8, 7.1, 7.4, 8.3, 6.3, 7.2, 6.5, 7.3, 7.9, 5.7, 6.5, 7.7, 4.3, 7.8, 7.8, 7.2, 5.0, 7.1, 5.7, 7.1, 6.0, 6.9, 7.9, 6.2, 7.2, 5.3, 4.7, 6.6, 7.0, 3.9, 6.6, 5.4, 6.4, 6.7, 6.9, 5.4, 7.0, 6.4, 7.2, 6.5, 7.0, 5.7, 7.3, 6.1, 7.2, 7.4, 6.3, 7.1, 5.7, 6.7, 6.8, 6.5, 6.8, 7.9, 5.8, 7.1, 4.3, 6.3, 7.1, 4.6, 7.1, 6.3, 6.9, 6.6, 6.5, 6.5, 6.8, 7.8, 6.1, 5.8, 6.3, 7.5, 6.1, 6.5, 6.0, 7.1, 7.1, 7.8, 6.8, 5.8, 6.8, 6.8, 7.6, 6.3, 4.9, 4.2, 5.1, 5.7, 7.6, 5.2, 7.2, 6.0, 7.3, 7.2, 7.8, 6.2, 7.1, 6.4, 6.1, 7.2, 6.6, 6.2, 7.9, 7.3, 6.7, 6.4, 6.4, 7.2, 5.1, 7.4, 7.2, 6.9, 8.1, 7.0, 6.2, 7.6, 6.7, 7.5, 6.6, 6.3, 4.0, 6.9, 6.3, 7.3, 7.3, 6.4, 6.6, 5.6, 6.0, 6.3, 6.7, 6.0, 6.1, 6.2, 6.7, 6.6, 7.0, 4.9, 8.4, 7.0, 7.5, 7.3, 5.6, 6.7, 8.0, 8.1, 4.8, 7.5, 5.5, 8.2, 6.6, 3.2, 5.3, 5.6, 7.4, 6.4, 6.8, 6.7, 6.4, 7.0, 7.9, 5.9, 7.7, 6.7, 7.0, 6.9, 7.7, 6.6, 7.1, 6.6, 5.7, 6.3, 6.5, 8.0, 6.1, 6.5, 7.6, 5.6, 5.9, 7.2, 6.7, 7.2, 6.5, 7.2, 6.7, 7.5, 6.5, 5.9, 7.7, 8.0, 7.6, 6.1, 8.3, 7.1, 5.4, 7.8, 6.5, 5.5, 7.9, 8.1, 6.1, 7.3, 7.2, 5.5, 6.5, 7.0, 7.1, 6.6, 6.5, 5.8, 7.1, 6.5, 7.4, 6.2, 6.0, 7.6, 7.3, 8.2, 5.8, 6.5, 6.6, 6.2, 5.8, 6.4, 6.7, 7.1, 6.0, 5.1, 6.2, 6.2, 6.6, 7.6, 6.8, 6.7, 6.3, 7.0, 6.9, 6.6, 7.7, 7.5, 5.6, 7.1, 5.7, 5.2, 5.4, 6.6, 8.2, 7.6, 6.2, 6.1, 4.6, 5.7, 6.1, 5.9, 7.2, 6.5, 7.9, 6.3, 5.0, 7.3, 5.2, 6.6, 5.2, 7.8, 7.5, 7.3, 7.3, 6.6, 5.7, 8.2, 6.7, 6.2, 6.3, 5.7, 6.6, 4.5, 8.1, 5.6, 7.3, 6.2, 5.1, 4.7, 4.8, 7.2, 6.9, 6.5, 7.3, 6.5, 6.9, 7.8, 6.8, 4.6, 6.7, 6.4, 6.0, 6.3, 6.6, 7.8, 6.6, 6.2, 7.3, 7.4, 6.5, 7.0, 4.3, 7.2, 6.2, 6.2, 6.8, 6.0, 6.6, 7.1, 6.8, 5.2, 6.7, 6.2, 7.0, 6.3, 7.8, 7.6, 5.4, 7.6, 5.4, 4.6, 6.9, 6.8, 5.8, 7.0, 5.8, 5.3, 4.6, 5.3, 7.6, 1.9, 7.2, 6.4, 7.4, 5.7, 6.4, 6.3, 7.5, 5.5, 4.2, 7.8, 6.3, 6.4, 7.1, 7.1, 6.8, 7.3, 6.7, 7.8, 6.3, 7.5, 6.8, 7.4, 6.8, 7.1, 7.6, 5.9, 6.6, 7.5, 6.4, 7.8, 7.2, 8.4, 6.2, 7.1, 6.3, 6.5, 6.9, 6.9, 6.6, 6.9, 7.7, 2.7, 5.4, 7.0, 6.6, 7.0, 6.9, 7.3, 5.8, 5.8, 6.9, 7.5, 6.3, 6.9, 6.1, 7.5, 6.8, 6.5, 5.5, 7.7, 3.5, 6.2, 7.1, 5.5, 7.1, 7.1, 7.1, 7.9, 6.5, 5.5, 6.5, 5.6, 6.8, 7.9, 6.2, 6.2, 6.7, 6.9, 6.5, 6.6, 6.4, 4.7, 7.2, 7.2, 6.7, 7.5, 6.6, 6.7, 7.5, 6.1, 6.4, 6.3, 6.4, 6.8, 6.1, 4.9, 7.3, 5.9, 6.1, 7.1, 5.9, 6.8, 5.4, 6.3, 6.2, 6.6, 4.4, 6.8, 7.3, 7.4, 6.1, 4.9, 5.8, 6.1, 6.4, 6.9, 7.2, 5.6, 4.9, 6.1, 7.8, 7.3, 4.3, 7.2, 6.4, 6.2, 5.2, 7.7, 6.2, 7.8, 7.0, 5.9, 6.7, 6.3, 6.9, 7.0, 6.7, 7.3, 3.5, 6.5, 4.8, 6.9, 5.9, 6.2, 7.4, 6.0, 6.2, 5.0, 7.0, 7.6, 7.0, 5.3, 7.4, 6.5, 6.8, 5.6, 5.9, 6.3, 7.1, 7.5, 6.6, 8.5, 6.3, 5.9, 6.7, 6.2, 5.5, 6.2, 5.6, 5.3])
max_runtime = runtime_data.max()
min_runtime = runtime_data.min()
print(min_runtime,max_runtime)
#设置不等宽的组距，hist方法中取到的会是一个左闭右开的去见[1.9,3.5)
num_bin_list = [1.9,3.5]
i=3.5
while i<=max_runtime:
    i += 0.5
    num_bin_list.append(i)
print(num_bin_list)
#设置图形的大小
plt.figure(figsize=(20,8),dpi=80)
plt.hist(runtime_data,num_bin_list)
#xticks让之前的组距能够对应上
plt.xticks(num_bin_list)
plt.show()