View source for Poverty and Inequality Platform, World Bank

== Summary ==
The [https://pip.worldbank.org/home Poverty and Inequality Platform (PIP)] is an interactive computational tool that offers users quick access to the World Bank’s estimates of poverty, inequality, and shared prosperity. PIP provides a comprehensive view of global, regional, and country-level trends for more than 160 economies around the world. All poverty and inequality indicators are organized under the dropdown “Data”, where users can access the different measures. The visualizations available allow for multiple ways to explore PIP indicators, from cross-country and regional analyses, to country-specific and subnational, while other pages provide in-depth analyses by topic.

We use this data for 7 series in IFs: 

# IncBelow2D15c%PIP
# IncBelow3D65c%PIP
# IncBelow6D85c%PIP
# IncMedPIP
# PovGap2D15cperDayPIP
# PovGap3D55cperDayPIP
# PovGap6D85cperDayPIP

== Data Pulling ==

# Go to this site. Make sure the mode is 2017 PPP. [[File:PIP .png|none|thumb|600x600px]]
# Select Poverty Rate. The data you need will show up in one excel (ie if you need the poverty rate and gap for $2.15, it will show up in one excel). You do not need to select any other indicator or countries. 
# Click Advanced options and choose Display Interpolated Values. Then click download and choose download all country data. While the excel file has different indicators you do need to download different excels for the different dollar amounts (you will have one excel for $2.15, another for $3.65, etc). [[File:PIP Advanced Options .png|none|thumb]]
# Filter your data by national (except for  Argentina, we can use urban data. For all the other countries it must be national.) headcount, poverty_gap, and median (median is the same in all excel files) will be the indicators for your data. 

== Notes ==
For the series: 

* IncBelow2D15c%PIP
* IncBelow3D65c%PIP
* IncBelow6D85c%PIP
* PovGap2D15cperDayPIP
* PovGap3D55cperDayPIP
* PovGap6D85cperDayPIP

Multiply the data points by 100 to get the percentage values. 

Turkiye must be correct to Turkey. 

For Argentina, we can use urban data. For all the other countries it must be national.