kiva: Kiva crowdfunding data

Description Usage Format Details Note Source Examples

Description

From the Kaggle website description: Kiva.org is an online crowdfunding platform to extend financial services to poor and financially excluded people around the world. Kiva lenders have provided over $1 billion dollars in loans to over 2 million people. In order to set investment priorities, help inform lenders, and understand their target communities, knowing the level of poverty of each borrower is critical. However, this requires inference based on a limited set of information for each borrower...

Usage

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Format

Several data frames combined by id: kiva_loans, kiva_mpi_region_locations, loan_theme_ids, loan_themes_by_region. Original names and descriptions are provided.

id

Unique ID for loan

funded_amount

The amount disbursed by Kiva to the field agent(USD)

activity

More granular category

sector

High level category

use

Exact usage of loan amount

country_code

ISO country code of country in which loan was disbursed

country

Full country name of country in which loan was disbursed

region

Full region name within the country

currency

The currency in which the loan was disbursed

partner_id

ID of partner organization

posted_time

The time at which the loan is posted on Kiva by the field agent

disbursed_time

The time at which the loan is disbursed by the field agent to the borrower

funded_time

The time at which the loan posted to Kiva gets funded by lenders completely

term_in_months

The duration for which the loan was disbursed in months

lender_count

The total number of lenders that contributed to this loan

tags

No description provided

borrower_genders

Comma separated Male, Female, where each instance represents a single male/female in the group. This was broken out into separate counts for male and female.

repayment_interval
date
LocationName

region, country

ISO

some sort of unique abbreviation for country

country

country

region

region with in country

world_region

parts of the world

MPI

multidimensional poverty index

geo

(latitude, longitude)

lat

latitude

lon

longitude

id

Unique ID for loan (Loan ID)

Loan Theme ID

ID for Loan Theme

Loan Theme Type

Category name of type of loan

Partner ID

Unique ID for field partners

Field Partner Name

No description provided.

sector

No description provided.

Loan Theme ID

No description provided.

Loan Theme Type

No description provided.

country

No description provided.

forkiva

No description provided.

region

No description provided.

geocode_old

No description provided.

ISO

No description provided.

number

No description provided.

amount

No description provided.

LocationName

No description provided.

geocode

No description provided.

names

No description provided.

geo

No description provided.

lat

No description provided.

lon

No description provided.

mpi_region

No description provided.

Details

Kiva has provided a dataset of loans issued over the last two years, and participants are invited to use this data as well as source external public datasets to help Kiva build models for assessing borrower welfare levels... With a stronger understanding of their borrowers and their poverty levels, Kiva will be able to better assess and maximize the impact of their work.

This is a merged version of the four data sets provided at Kaggle. I began with the largest dataset, loan_theme_ids, and joined the others by id to that one. While most did ids had a match across datasets, many did not match.

In terms of cleanup, the 'geo' variables were removed as they were just text strings of latitude and longitude coordinates. The borrower_genders column was broken out into male and female counts. Where possible, strings were converted to integer or date formats. Column names were made more appropriate, and rearranged to reflect conceptual information.

More context on the variables can be found at the links below, but specific information is sparse.

Known issues: Some character strings may have formatting issues.

Note

License is CC0

Source

Data link.

Examples

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m-clark/noiris documentation built on Sept. 9, 2019, 9:08 a.m.