air pollution data for delhi as csv

[Debamitro Chakraborti]

From tomorrow the Delhi govt will try an odd-even scheme for private vehicles entering the city. It might be helpful to have csv data of December and January for air pollution. CPCB does give the data in the site http://www.cpcb.gov.in/CAAQM/mapPage/frmdelhi.aspx?stateID=6 and sometimes an advance search works there as well - but I couldn't find a way of getting csv data.

Regards,

Debamitro

[Sarath Guttikunda]

Dear All,

good morning.

For PM2.5, DPCC stations are more accessible than the CPCB stations

http://www.dpccairdata.com

Attached is the archives from 2013, 2014, and 2015 - raw data, as archived.

The quality of the data from the airport station is not so good, a lot of weeding is required.

There are couple of other places where you can download the data for Delhi

http://www.delhiairquality.info/monitoring-data/

With regards,

Sarath

--
Dr. Sarath Guttikunda
http://www.urbanemissions.info

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[Nikhil VJ]

Also check out this citizen powered air quality monitoring effort:

http://breathe.indiaspend.org/

Cheers,
Nikhil VJ
+91 966 583 1250
http://nikhilsheth.blogspot.in

[shantanu oak]

Similar data is also available from US Embassy.

http://newdelhi.usembassy.gov/airqualitydataemb.html

Use python to read and process the data.

# import modules

%pylab inline

import pandas as pd

import numpy as np

from urllib import urlopen

import matplotlib.pyplot as plt

# open csv file from the web

url='http://newdelhi.usembassy.gov/airqualitydataemb/aqm2014.csv'

tips=pd.read_csv(urlopen(url), skiprows=2, skip_footer=8, parse_dates=[['Date', 'Time']])

 

# clean up data

tips=tips.replace('NoData', np.nan)

tips=tips.fillna(method='pad')

tips = tips.ix[2:]

tips=tips.set_index(['Date_Time'])

tips['US Embassy-New Delhi'] = tips['US Embassy-New Delhi'].astype(integer)

# create charts based on first 50 rows

tips[['US Embassy-New Delhi']][:50].plot()

-- Shantanu Oak

[shantanu oak]

I am attaching a zip file abc.csv that has merged data across all 2015 csv files sent by Dr. Sarath. 

This python code was used.

import os

mylist=[]

indir = '/home/ubuntu/syllabalize_unicode/monitor/'

for root, dirs, filenames in os.walk(indir):

    for f in filenames:

        if f.endswith('csv') and f.startswith('2015'):

            mylist.append(root+f)

dflist=[]

import pandas as pd

for i in mylist:

    col_name = i.replace('_', '').split('/')[5].split('.')[0]

    i=pd.read_csv(i, parse_dates=['Date'])

    i.columns = ['sample', col_name, 'Date' ]

    i=i[[col_name, 'Date']]

    i=i.fillna(method='pad')

    i=i.set_index(['Date'])

    dflist.append(i)

merged_df=pd.concat( dflist, axis=1)

merged_df.to_csv('/var/www/html/abc.csv')

-- Shantanu Oak