吴裕雄--天生自然 PYTHON数据分析：医疗数据分析

import numpy as np # linear algebra
import pandas as pd # data processing,CSV file I/O (e.g. pd.read_csv)

# plotly
import chart_studio.plotly as py
from plotly.offline import init_notebook_mode,iplot
init_notebook_mode(connected=True)
import plotly.graph_objs as go
import seaborn as sns
# word cloud library
from wordcloud import WordCloud

# matplotlib
import matplotlib.pyplot as plt
# Input data files are available in the "../input/" directory.
# For example,running this (by clicking run or pressing Shift+Enter) will list the files in the input directory

dataframe = pd.read_csv("F:kaggleDataSethealthcare-datatest_2v.csv")

import chart_studio.plotly as py
from plotly.graph_objs import *

df_heart_disease = dataframe[dataframe.heart_disease== 1] 
labels = df_heart_disease.gender
pie1_list=df_heart_disease.heart_disease

df_hypertension= dataframe[dataframe.hypertension == 1] 
labels1 = df_hypertension.gender
pie1_list1=df_hypertension.hypertension


labels2 = dataframe.Residence_type
pie1_list2 = dataframe.heart_disease

labels3 = dataframe.work_type
pie1_list3 = dataframe.heart_disease



fig = {
    ‘data‘: [
        {
            ‘labels‘: labels,‘values‘: pie1_list,‘type‘: ‘pie‘,‘name‘: ‘Heart Disease‘,‘marker‘: {‘colors‘: [‘rgb(56,75,126)‘,‘rgb(18,36,37)‘,‘rgb(34,53,101)‘,‘rgb(36,55,57)‘,‘rgb(6,4,4)‘]},‘domain‘: {‘x‘: [0,.48],‘y‘: [0,.49]},‘hoverinfo‘:‘label+percent+name‘,‘textinfo‘:‘none‘
        },{
            ‘labels‘: labels1,‘values‘: pie1_list1,‘marker‘: {‘colors‘: [‘rgb(177,127,38)‘,‘rgb(205,152,36)‘,‘rgb(99,79,‘rgb(129,180,179)‘,‘rgb(124,103,37)‘]},‘name‘: ‘Hypertension‘,‘domain‘: {‘x‘: [.52,1],‘textinfo‘:‘none‘

        },{
            ‘labels‘: labels2,‘values‘: pie1_list2,‘marker‘: {‘colors‘: [‘rgb(33,99)‘,‘rgb(79,129,102)‘,‘rgb(151,179,100)‘,‘rgb(175,49,35)‘,73,147)‘]},‘name‘: ‘Residence Type‘,‘y‘: [.51,1]},{
            ‘labels‘: labels3,‘values‘: pie1_list3,‘marker‘: {‘colors‘: [‘rgb(146,123,21)‘,‘rgb(177,34)‘,‘rgb(206,206,40)‘,51,‘rgb(35,21)‘]},‘name‘:‘Work Type‘,‘textinfo‘:‘none‘
        }
        
    ],‘layout‘: {‘title‘: ‘‘,‘showlegend‘: False}
}

iplot(fig)

import chart_studio.plotly as py
import plotly.graph_objs as go

# Create random data with numpy
import numpy as np

df_250 = dataframe.iloc[:250,:]


random_x = df_250.index
random_y0 =  df_250.avg_glucose_level
random_y1 =  df_250.bmi
random_y2 =  df_250.age

# Create traces
trace0 = go.Scatter(
    x = random_x,y = random_y0,mode = ‘markers‘,name = ‘Avg. Glucose Level‘
)
trace1 = go.Scatter(
    x = random_x,y = random_y1,mode = ‘lines+markers‘,name = ‘BMI‘
)
trace2 = go.Scatter(
    x = random_x,y = random_y2,mode = ‘lines‘,name = ‘Age‘
)

data = [trace0,trace1,trace2]
iplot(data,filename=‘scatter-mode‘)

import chart_studio.plotly as py
import plotly.graph_objs as go
df_heart_disease = dataframe[dataframe.heart_disease==1] 
labels = df_heart_disease.gender
x = labels

trace0 = go.Box(
    y=dataframe.age,x=x,name=‘Age‘,marker=dict(
        color=‘#3D9970‘
    )
)
trace1 = go.Box(
    y=dataframe.avg_glucose_level,name=‘Avg. Glucose Level‘,marker=dict(
        color=‘#FF4136‘
    )
)
trace2 = go.Box(
    y=dataframe.bmi,name=‘BMI‘,marker=dict(
        color=‘#FF851B‘
    )
)
data = [trace0,trace2]
layout = go.Layout(
    yaxis=dict(
        title=‘Attendants Who Has Heart Disease‘,zeroline=False
    ),boxmode=‘group‘
)
fig = go.Figure(data=data,layout=layout)
iplot(fig)

import chart_studio.plotly as py
import plotly.graph_objs as go
df_hypertension= dataframe[dataframe.hypertension == 1] 
labels1 = df_hypertension.gender
x = labels1

trace0 = go.Box(
    y=dataframe.age,trace2]
layout = go.Layout(
    yaxis=dict(
        title=‘Attendants Who Has Hypertension‘,layout=layout)
iplot(fig)

df_heart_disease_1 = dataframe.smoking_status [dataframe.heart_disease == 1  ]        
df_hypertension_1  = dataframe.smoking_status [dataframe.hypertension  == 1   ]       
trace1 = go.Histogram(
    x=df_heart_disease_1,opacity=0.75,name = "Heart Disease",marker=dict(color=‘rgba(171,50,96,0.6)‘))
trace2 = go.Histogram(
    x=df_hypertension_1,name = "Hypertension",marker=dict(color=‘rgba(12,196,0.6)‘))



data = [trace1,trace2]
layout = go.Layout(barmode=‘overlay‘,title=‘ Association Between Smoking,Heart Disease & Hypertension‘,xaxis=dict(title=‘Smoking Status‘),yaxis=dict( title=‘Attendants‘),)
fig = go.Figure(data=data,layout=layout)
iplot(fig)

df_heart_disease_1 = dataframe.work_type [dataframe.heart_disease    == 1  ]        
df_hypertension_1 = dataframe.work_type [dataframe.hypertension    == 1   ]     

trace1 = go.Histogram(
    x=df_heart_disease_1,0.6)‘))

data = [trace1,title=‘ Association Between Work Type,xaxis=dict(title=‘‘),layout=layout)
iplot(fig)