how to read and parse the csv files using pandas in django

import pandas as pd
import seaborn as sns
import matplotlib.pyplot as plt
import calendar
import numpy as np
import time
crimes=pd.read_csv(r"D:\python\Project\data.csv")
crimes.head(2)

crimes.describe()
crimes.drop(['Unnamed: 0', 'Case Number','Block','IUCR', 'X Coordinate', 'Y Coordinate','Updated On', 'FBI Code', 'Beat','Ward','Community Area', 'Location','Latitude','Longitude','District'], inplace=True, axis=1)
crimes.head(4)
crimes=crimes[(crimes['Year']==2016)|(crimes['Year']==2015)]
crimes.describe()
f=plt.figure(1)
sns.countplot(x='Year',data=crimes)
plt.ylabel('No of Crimes')
f.show()
f1=plt.figure(2)
crimes['Date'] = pd.to_datetime(crimes['Date'],format='%m/%d/%Y %I:%M:%S %p')
crimes['Month']=(crimes['Date'].dt.month).apply(lambda x: calendar.month_abbr[x])
crimes.head(4)
crimes['Month'] = pd.Categorical(crimes['Month'] , categories=['Jan','Feb','Mar','Apr','May','Jun','Jul','Aug','Sep','Oct','Nov','Dec'], ordered=True)
months=['Jan','Feb','Mar','Apr','May','Jun','Jul','Aug','Sep','Oct','Nov','Dec']
crimes.groupby('Month')['ID'].count().plot(marker='o')
plt.xticks(np.arange(12),months)
plt.ylabel('No of Crimes')
f1.show()

f3=plt.figure(3)
crimes["Weekday"] = crimes['Date'].dt.weekday_name
crimes['Weekday'] = pd.Categorical(crimes['Weekday'],categories=['Monday','Tuesday','Wednesday','Thursday','Friday','Saturday', 'Sunday'], ordered=True)
crimes.head()
crimes.groupby('Weekday')['ID'].count().plot(marker='o',label='Crimes')
plt.ylabel('No of Crimes')
f3.show()
f4=plt.figure(4)
sns.countplot(x='Primary Type',data=crimes,order=crimes['Primary Type'].value_counts().index)
plt.xticks(rotation='vertical')
plt.ylabel('No of Crimes')
f4.show()
f5=plt.figure(5)
temp=crimes.groupby('Location Description')['ID'].count().sort_values(ascending=False)
temp=temp[:10]
temp
temp.plot(kind='bar',color='green')
plt.ylabel('No of Crimes')
f5.show()
f7=plt.figure(6)
sns.countplot(x='Arrest',data=crimes)
plt.ylabel('No of Crimes')
f7.show()

f9=plt.figure(7)
sns.set(rc={'figure.figsize':(12,6)})
sns.countplot(x='Primary Type',hue='Arrest',data=crimes,order=crimes['Primary Type'].value_counts().index)
plt.xticks(rotation='vertical')
plt.ylabel('No of Crimes')
f9.show()
f10=plt.figure(8)
arrest=crimes[crimes['Arrest']==True]
arrest.info()
arrest.groupby('Month')['ID'].count().plot(legend=True,label='Arrests',marker='o',figsize=(8,6))
crimes.groupby('Month')['ID'].count().plot(legend=True,label='Crimes',marker='o')
plt.ylabel('No of Crimes')
plt.xticks(np.arange(12),months)
f10.show()
f11=plt.figure(9)
arrest.groupby('Month')['ID'].count()
crimes.groupby('Month')['ID'].count()
top_crime=crimes[(crimes['Primary Type']=='THEFT')|(crimes['Primary Type']=='BATTERY')|(crimes['Primary Type']=='CRIMINAL DAMAGE')|(crimes['Primary Type']=='NARCOTICS')|(crimes['Primary Type']=='ASSAULT')]
temp=top_crime.pivot_table(values='ID', index='Month', columns='Year', aggfunc=np.size)
sns.heatmap(temp)
f11.show()

f13=plt.figure(10)
temp= top_crime.pivot_table(values='ID', index='Primary Type',columns=top_crime['Date'].dt.hour, aggfunc=np.size)
sns.heatmap(temp)
plt.xlabel('Hours of the day')
plt.ylabel('Type of Crime')
f13.show()

I have normal python code to plot the graphs for csv data(data visualisation).But I need code in django and graphs should display on dashboard...

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