输出结果
实现代码
# coding: utf8
import pandas as pd
import matplotlib.pyplot as plt
# ML之FE：对人类性别相关属性数据集进行数据特征分布可视化分析与挖掘
#1、定义数据集
# 头发(长发/短发)、身高、下巴(棱角/圆滑)、胡长(mm)、皮肤、体重
contents={"name": ['Mary', 'Bob', 'Lisa', 'Tom', 'Alan', 'Jason','Sophia', 'Aiden', 'Sarah', 'Miqi', 'Temp01', 'Temp02'],
"age": [ 16, 24, 19, 20, 33, 23, 29, 31, 34, 24, 27, 30],
"Hair": ['长发', '短发', '长发', '短发', '长发', '短发', '长发', '长发', '长发', '长发', '短发', '长发'],
"Height": [158, 175, 162, 170, 175, 168, 166, 169, 164, 157, 182, 161],
"Jaw": ['圆滑', '棱角', '圆滑', '棱角', '圆滑', '圆滑', '圆滑', '棱角', '圆滑', '圆滑', '棱角', '圆滑'],
"Beard": [2, 7, 3, 5, 2, 3, 5, 6, 3, 4, 5, 3],
"Skin": ['细腻', '粗糙', '细腻', '粗糙', '细腻', '粗糙', '细腻', '粗糙', '细腻', '细腻', '粗糙', '粗糙'],
"Weight": [99, 143, 105, 135, 120, 160, 95, 145, 125, 112, 155, 100],
"Sex": ['女性', '男性', '女性', '男性', '男性', '男性', '女性', '男性', '女性', '女性', '男性', '女性'],
}
data_frame = pd.DataFrame(contents)
print(type(data_frame))
data_name = 'HumanGender_RelatedAttributes'
col_cat='Jaw'
label_name='Sex'
for col in data_frame.columns[1:-2]:
if data_frame[col].dtypes in ['object']:
print(col)
# T1、采用函数
col_cats=[col,label_name]
# SNCountPlot(col_cats,data_frame,imgName='')
# T2、自定义函数？？？
x_subname = list(data_frame[col].value_counts().to_dict().keys())
label_y1 = list(data_frame[label_name].value_counts().to_dict().keys())[0]
label_y2 = list(data_frame[label_name].value_counts().to_dict().keys())[1]
y1=list(data_frame[data_frame[label_name]==label_y1][col].value_counts().to_dict().values())
y2=list(data_frame[data_frame[label_name]==label_y2][col].value_counts().to_dict().values())
print(x_subname)
print(label_y1,label_y2)
print(y1,y2)
# # T2、自定义函数？？？
# y01Lists,y02Lists=[],[]
# for x in x_subname:
# if x not in data_frame[data_frame[label_name]==label_y2][col].value_counts(dropna=False).to_dict().keys():
# pass
# else:
#
# y01=data_frame[data_frame[label_name]==label_y1][col].value_counts(dropna=False).to_dict()[x]
# y02=data_frame[data_frame[label_name]==label_y2][col].value_counts(dropna=False).to_dict()[x]
# y01Lists.append(y01)
# y02Lists.append(y02)
# print(y01Lists,y02Lists)
DoubleBarAddText(y1,y2, col,label_name, x_subname,label_y1,label_y2,data_name)
else:
Num_col_Plot2_ByLabels(data_name,data_frame,label_name,col)
