Презентация на тему Data Visualization For Social Problems

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Слайд 1DATA VISUALIZATION
FOR SOCIAL PROBLEMS
S Anand, Chief Data Scientist, Gramener

DATA VISUALIZATIONFOR SOCIAL PROBLEMS	S Anand, Chief Data Scientist, Gramener

Слайд 2


Слайд 4
Most discussions of decision-making assume that only senior executives make decisions

or that only senior executives’ decisions matter. This is a dangerous mistake…


Peter F Drucker

Data generation and analysis are not sufficient.
Consuming it as a team and acting in cohesion is.

Most discussions of decision-making assume that only senior executives make decisions or

Слайд 5SHOW
me what is happening with the data
EXPLAIN
to me why it’s happening
Allow

me to
EXPLORE
and figure it out

Just
EXPOSE
the data to me

Low effort

High effort

High effort

Low effort

Creator

Consumer

There are many ways to aid data consumption

SHOWme what is happening with the dataEXPLAINto me why it’s happeningAllow me

Слайд 6SHOW
me what is happening with the data
EXPLAIN
to me why it’s happening
Allow

me to
EXPLORE
and figure it out

Just
EXPOSE
the data to me

SHOWme what is happening with the dataEXPLAINto me why it’s happeningAllow me

Слайд 10SHOW
me what is happening with the data
EXPLAIN
to me why it’s happening
Allow

me to
EXPLORE
and figure it out

Just
EXPOSE
the data to me

SHOWme what is happening with the dataEXPLAINto me why it’s happeningAllow me

Слайд 11EDUCATION
PREDICTING MARKS
What determines a child’s marks?
Do girls score better than boys?
Does

the choice of subject matter?
Does the medium of instruction matter?
Does community or religion matter?
Does their birthday matter?
Does the first letter of their name matter?
EDUCATIONPREDICTING MARKSWhat determines a child’s marks?Do girls score better than boys?Does the

Слайд 12TN Class X: English

TN Class X: English

Слайд 13TN Class X: Social Science

TN Class X: Social Science

Слайд 14TN Class X: Mathematics

TN Class X: Mathematics

Слайд 17DETECTING FRAUD
ENERGY UTILITY

DETECTING FRAUDENERGY UTILITY

Слайд 18This plot shows the frequency of all meter readings from Apr-2010

to Mar-2011. An unusually large number of readings are aligned with the tariff slab boundaries.

This clearly shows collusion of some form with the customers.

This happens with specific customers, not randomly. Here are such customers’ meter readings.

If we define the “extent of fraud” as the percentage excess of the 100 unit

meter reading, the value varies considerably across sections, and time

New section manager arrives

… and is transferred out

… with some explainable anomalies.

Why would these happen?

This plot shows the frequency of all meter readings from Apr-2010 to

Слайд 19SHOW
me what is happening with the data
EXPLAIN
to me why it’s happening
Allow

me to
EXPLORE
and figure it out

Just
EXPOSE
the data to me

… to inform and to entertain

SHOWme what is happening with the dataEXPLAINto me why it’s happeningAllow me

Слайд 20SHOW
me what is happening with the data
EXPLAIN
to me why it’s happening
Allow

me to
EXPLORE
and figure it out

Just
EXPOSE
the data to me

SHOWme what is happening with the dataEXPLAINto me why it’s happeningAllow me

Слайд 22Jain
Harini
Shweta
Sneha
Pooja
Ashwin
Shah
Deepti
Sanjana
Varshini
Ezhumalai
Venkatesan
Silambarasan
Pandiyan
Kumaresan
Manikandan
Thirupathi
Agarwal
Kumar
Priya

JainHariniShwetaSnehaPoojaAshwinShahDeeptiSanjanaVarshiniEzhumalaiVenkatesanSilambarasanPandiyanKumaresanManikandanThirupathiAgarwalKumarPriya

Слайд 23
 

Based on the results of the 20 lakh students taking the

Class XII exams at Tamil Nadu over the last 3 years, it appears that the month you were born in can make a difference of as much as 120 marks out of 1,200.

June borns score the lowest

The marks shoot up for Aug borns

… and peaks for Sep-borns

120 marks out of 1200 explainable by month of birth

An identical pattern was observed in 2009 and 2010…

… and across districts, gender, subjects, and class X & XII.

“It’s simply that in Canada the eligibility cutoff for age-class hockey is January 1. A boy who turns ten on January 2, then, could be playing alongside someone who doesn’t turn ten until the end of the year—and at that age, in preadolescence, a twelve-month gap in age represents an enormous difference in physical maturity.”
-- Malcolm Gladwell, Outliers

 Based on the results of the 20 lakh students taking the Class

Слайд 24Let’s look at 15 years of US Birth Data
This is a

dataset (1975 – 1990) that has been around for several years, and has been studied extensively. Yet, a visualization can reveal patterns that are neither obvious nor well known.

For example,
Are birthdays uniformly distributed?
Do doctors or parents exercise the C-section option to move dates?
Is there any day of the month that has unusually high or low births?
Are there any months with relatively high or low births?

Very high births in September. But this is fairly well known. Most conceptions happen during the winter holiday season

Relatively few births during the Christmas and Thanksgiving holidays, as well as New Year and Independence Day.

Most people prefer not to have children on the 13th of any month, given that it’s an unlucky day

Some special days like April Fool’s day are avoided, but Valentine’s Day is quite popular



More births

Fewer births

… on average, for each day of the year (from 1975 to 1990)

Let’s look at 15 years of US Birth DataThis is a dataset

Слайд 25The pattern in India is quite different
This is a birth date

dataset that’s obtained from school admission data for over 10 million children. When we compare this with births in the US, we see none of the same patterns.

For example,
Is there an aversion to the 13th or is there a local cultural nuance?
Are holidays avoided for births?
Which months have a higher propensity for births, and why?
Are there any patterns not found in the US data?

Very few children are born in the month of August, and thereafter. Most births are concentrated in the first half of the year

We see a large number of children born on the 5th, 10th, 15th, 20th and 25th of each month – that is, round numbered dates

Such round numbered patterns a typical indication of fraud. Here, birthdates are brought forward to aid early school admission



More births

Fewer births

… on average, for each day of the year (from 2007 to 2013)

The pattern in India is quite differentThis is a birth date dataset

Слайд 26This adversely impacts children’s marks
It’s a well established fact that older

children tend to do better at school in most activities. Since many children have had their birth dates brought forward, these younger children suffer.

The average marks of children “born” on the 1st, 5th, 10th, 15th etc. of the month tend to score lower marks.
Are holidays avoided for births?
Which months have a higher propensity for births, and why?
Are there any patterns not found in the US data?



Higher marks

Lower marks

… on average, for children born on a given day of the year (from 2007 to 2013)

Children “born” on round numbered days score lower marks on average,
due to a higher proportion of younger children

This adversely impacts children’s marksIt’s a well established fact that older children

Слайд 27# contestants
Winner margin
More contestants did not reduce the winner margin
Karnataka, Assembly

Elections 2008
# contestantsWinner marginMore contestants did not reduce the winner marginKarnataka, Assembly Elections 2008

Слайд 28# contestants
Runner-up margin
More contestants did reduce the runner-up margin
Karnataka, Assembly Elections

2004
# contestantsRunner-up marginMore contestants did reduce the runner-up marginKarnataka, Assembly Elections 2004

Слайд 29
Adult Education
Adminisrative Reforms
Agricultural Marketing
Agriculture
Animal Husbandry

Cooperative

Excise
Finance
Fisheries
Fisheries & Inland water transport
Food & Civil

Supplies

Forest

Fuel

Haz & Wakf

Health and family welfare

Higher Education

Home

Horticulture

Housing


Information & Technology

Kannada & Culture

Labour

Law & Human Rights


Major & Medium Industries

Medical Education

Medium and Large Industries

Mines & Geology

Minor Irrigation

Muzrai

P.W.D.

Parliamentary Affairs and Human Rights

Planning

Planning and Statistics

Primary and Secondary Education

Primary Education

Prison

Public Library

Revenue

Rural Development and Panchayat Raj

Rural Water Supply

Rural Water Supply and Sanitation

Sericulture

Small Scale Industries

Small Industries

Social Welfare

Sugar

Textile

Tourism

Transport

Transportation

Urban Development

Water Resources

Woman & Child Development

Youth and Sports

Youth Service & Sports

BJP focus

JD(S)
focus

INC focus

What topics did parties focus on during questions?

Karnataka, 2008-2012

Adult EducationAdminisrative ReformsAgricultural MarketingAgricultureAnimal HusbandryCooperativeExciseFinanceFisheriesFisheries & Inland water transportFood & Civil SuppliesForestFuelHaz

Слайд 30P.W.D.
Health and family welfare
Revenue
Rural Development and Panchayat Raj
Social Welfare
Urban Development
Water Resources
Minor

Irrigation

Fuel

Housing

Agriculture

Primary Education

Primary and Secondary Education

Woman & Child Development

Higher Education

Home

Cooperative

Forest

Adminisrative Reforms

Labour

Food & Civil Supplies

Tourism

Finance

Animal Husbandry

Transportation

Horticulture

Muzrai

Haz & Wakf

Transport

Medical Education

Medium and Large Industries

Excise

Major & Medium Industries

Kannada & Culture

Textile

Fisheries

Parliamentary Affairs and Human Rights

Adult Education

Rural Water Supply and Sanitation

Mines & Geology

Small Industries

Youth and Sports

Sugar

Planning and Statistics

Agricultural Marketing

Rural Water Supply

Fisheries & Inland water transport

Small Scale Industries

Youth Service & Sports

Sericulture

Law & Human Rights

Prison

Planning

Information & Technology

Public Library





What topics did the young & old focus on during questions?

Karnataka, 2008-2012

Young

Old

P.W.D.Health and family welfareRevenueRural Development and Panchayat RajSocial WelfareUrban DevelopmentWater ResourcesMinor IrrigationFuelHousingAgriculturePrimary

Слайд 31SHOW
me what is happening with the data
EXPLAIN
to me why it’s happening
Allow

me to
EXPLORE
and figure it out

Just
EXPOSE
the data to me

… to connect the dots for your readers

SHOWme what is happening with the dataEXPLAINto me why it’s happeningAllow me

Слайд 32SHOW
me what is happening with the data
EXPLAIN
to me why it’s happening
Allow

me to
EXPLORE
and figure it out

Just
EXPOSE
the data to me

SHOWme what is happening with the dataEXPLAINto me why it’s happeningAllow me

Слайд 37https://gramener.com/aapdonations

https://gramener.com/aapdonations

Слайд 40EXPLORING THE MAHABHARATA
How does Mahabharata, one of the largest epics with

1.8 million words lend itself to text analytics?
Can this ‘unstructured data’ be processed to extract analytical insights?
What does sentiment analysis of this tome convey?
Is there a better way to explore relations between characters?
How can closeness of characters be analysed & visualized?
EXPLORING THE MAHABHARATAHow does Mahabharata, one of the largest epics with 1.8

Слайд 41SHOW
me what is happening with the data
EXPLAIN
to me why it’s happening
Allow

me to
EXPLORE
and figure it out

Just
EXPOSE
the data to me

… to allow your users to tell stories

SHOWme what is happening with the dataEXPLAINto me why it’s happeningAllow me

Слайд 42VISUALISATION IS IMPERATIVE FOR
DATA → INSIGHTS → ACTION
Spot the unusual
Communicate patterns
Simplify

decisions
VISUALISATION IS IMPERATIVE FORDATA → INSIGHTS → ACTIONSpot the unusualCommunicate patternsSimplify decisions

Слайд 43We handle terabyte-size data
via non-traditional analytics
and visualise it in real-time.
A data

analytics and visualisation company

gramener.com
for more examples

We handle terabyte-size datavia non-traditional analyticsand visualise it in real-time.A data analytics

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