Data Science: Data Visualization Boot CampComparison

Linear Charts

Chuck Cartledge, PhDChuck Cartledge, PhDChuck Cartledge, PhDChuck Cartledge, PhDChuck Cartledge, PhDChuck Cartledge, PhDChuck Cartledge, PhDChuck Cartledge, PhDChuck Cartledge, PhDChuck Cartledge, PhDChuck Cartledge, PhDChuck Cartledge, PhDChuck Cartledge, PhDChuck Cartledge, PhDChuck Cartledge, PhDChuck Cartledge, PhDChuck Cartledge, PhDChuck Cartledge, PhDChuck Cartledge, PhDChuck Cartledge, PhDChuck Cartledge, PhD

26 January 202026 January 202026 January 202026 January 202026 January 202026 January 202026 January 202026 January 202026 January 202026 January 202026 January 202026 January 202026 January 202026 January 202026 January 202026 January 202026 January 202026 January 202026 January 202026 January 202026 January 2020

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Table of contents (1 of 1)

1 TypeUsesGeneral considerations

2 Sample data

3 Hands on

4 Q & A

5 Conclusion6 References7 Files

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A definition

“Sometimes referred to as a curve graph.Line graphs are a family of graphs that dis-play quantitative information by means oflines. They are extremely versatile and there-fore are used extensively. . . . A simple linegraph displays a single data series. It typi-cally has a quantitative scale on the verticalaxis and a category, quantitative, or sequencescale on the horizontal axis.”

R. L. Harris [2]

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Groundwater Level Monitoring (1 of 2)

“Water table groundwater observation

wells are used to monitor shallow groundwa-

ter responses to drought conditions in each

drought evaluation region. In areas west of

Route I-95, wells completed in shallow frac-

tured rock formations are indicative of wa-

ter table conditions. In the Virginia Coastal

Plain area east of I-95, indicator observa-

tion wells are completed in the shallow un-

confined aquifer. For each observation well,

measured groundwater levels are compared

with historic groundwater level statistics for

the period of record.”

Va. DEQ Staff [3]

We select the sites of interest, using:

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Groundwater Level Monitoring (2 of 2)

https://www.deq.virginia.gov/Programs/Water/

WaterSupplyWaterQuantity/Drought/

DroughtIndicatorsandRegions/GroundwaterLevels.aspx

https://www.deq.virginia.gov/Programs/Water/WaterSupplyWaterQuantity/Drought/DroughtIndicatorsandRegions/GroundwaterLevels.aspxhttps://www.deq.virginia.gov/Programs/Water/WaterSupplyWaterQuantity/Drought/DroughtIndicatorsandRegions/GroundwaterLevels.aspxhttps://www.deq.virginia.gov/Programs/Water/WaterSupplyWaterQuantity/Drought/DroughtIndicatorsandRegions/GroundwaterLevels.aspx

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Selecting site of interest

https:

//groundwaterwatch.usgs.

gov/AWLSites.asp?mt=g&S=

363928076332901&ncd=awl

https:

//nwis.waterdata.usgs.gov/

nwis/dv?format=gif_meas&

site_no=363928076332901&

referred_module=gw

https://groundwaterwatch.usgs.gov/AWLSites.asp?mt=g&S=363928076332901&ncd=awlhttps://groundwaterwatch.usgs.gov/AWLSites.asp?mt=g&S=363928076332901&ncd=awlhttps://groundwaterwatch.usgs.gov/AWLSites.asp?mt=g&S=363928076332901&ncd=awlhttps://groundwaterwatch.usgs.gov/AWLSites.asp?mt=g&S=363928076332901&ncd=awlhttps://nwis.waterdata.usgs.gov/nwis/dv?format=gif_meas&site_no=363928076332901&referred_module=gwhttps://nwis.waterdata.usgs.gov/nwis/dv?format=gif_meas&site_no=363928076332901&referred_module=gwhttps://nwis.waterdata.usgs.gov/nwis/dv?format=gif_meas&site_no=363928076332901&referred_module=gwhttps://nwis.waterdata.usgs.gov/nwis/dv?format=gif_meas&site_no=363928076332901&referred_module=gwhttps://nwis.waterdata.usgs.gov/nwis/dv?format=gif_meas&site_no=363928076332901&referred_module=gw

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The data at last.

We:

1 Identified the sites/wells ofinterest

2 Selected the data type anddates of interest

3 Submitted the request fordata

4 Scrapped the resulting htmlfor the data of interest

All these steps are in theextractWaterLevels.R scriptfile.

Using the URL on the next slide.

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Sample URL to download data:

https:

//nwis.waterdata.usgs.gov/nwis/dv?cb_72019=on&format=

rdb_meas&site_no=363928076332901&referred_module=gw&

period=&begin_date=1981-01-20&end_date=2018-07-20

363928076332901 is the site identifier, and will change based onthe selected site.

https://nwis.waterdata.usgs.gov/nwis/dv?cb_72019=on&format=rdb_meas&site_no=363928076332901&referred_module=gw&period=&begin_date=1981-01-20&end_date=2018-07-20https://nwis.waterdata.usgs.gov/nwis/dv?cb_72019=on&format=rdb_meas&site_no=363928076332901&referred_module=gw&period=&begin_date=1981-01-20&end_date=2018-07-20https://nwis.waterdata.usgs.gov/nwis/dv?cb_72019=on&format=rdb_meas&site_no=363928076332901&referred_module=gw&period=&begin_date=1981-01-20&end_date=2018-07-20https://nwis.waterdata.usgs.gov/nwis/dv?cb_72019=on&format=rdb_meas&site_no=363928076332901&referred_module=gw&period=&begin_date=1981-01-20&end_date=2018-07-20

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Federal Reserve Economic Data (1 of 2)

“The Federal Reserve Bank of St. Louis is

the center of the Eighth District of the Federal

Reserve System. . . . The Division monitors the

economic and financial literature and produces

research in the areas of money and banking,

macroeconomics, and international and regional

economics. . . . The Research Division also fur-

nishes its working papers to provide insight into

current Bank interests and developing theories

and to stimulate discussion. . . . The widely used

database FRED is updated regularly and allows

24/7 access to regional and national financial and

economic data.”

Fed. Res. Bank Staff [1]

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Federal Reserve Economic Data (2 of 2)

We select the data of interest. https://fred.stlouisfed.org

https://fred.stlouisfed.org

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Selecting data of interest

For manual, singular download: https:

//fred.stlouisfed.org/series/PCE

For programtic, singular download:

https:

//github.com/tidyverse/ggplot2/

blob/master/data-raw/economics.R

We elected to download a series programtically.

https://fred.stlouisfed.org/series/PCEhttps://fred.stlouisfed.org/series/PCEhttps://github.com/tidyverse/ggplot2/blob/master/data-raw/economics.Rhttps://github.com/tidyverse/ggplot2/blob/master/data-raw/economics.Rhttps://github.com/tidyverse/ggplot2/blob/master/data-raw/economics.R

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The first codes. (1 of 5)

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The first codes. (2 of 5)

rm(list=ls())

library(ggplot2)

saveFileName

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The first codes. (3 of 5)

"DroughtIndicatorsandRegions/",

"GroundwaterLevels.aspx"),

colour="Sites of interest"

) +

theme(plot.title=element_text(hjust = 0.5)) +

theme(plot.title=element_text(colour = "blue")) +

theme(plot.subtitle=element_text(hjust = 0.5)) +

theme(plot.subtitle=element_text(colour = "black")) +

theme(plot.caption=element_text(hjust = 0.0)) +

theme(plot.caption=element_text(colour = "red")) +

theme(legend.title.align=0.5) +

theme(axis.text.x=element_text(angle=0, hjust = 0))

g + geom_point()

g + geom_line()

g + geom_line() +

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The first codes. (4 of 5)

scale_color_manual(

values=c("red", "blue"),

labels=c("Pungo", "Brinkley")

)

xMin

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The first codes. (5 of 5)

g + geom_line() +

xlim(xMin, xMax) +

scale_color_manual(

values=c("red", "blue"),

labels=c("Pungo", "Brinkley")

) +

scale_x_continuous(name="Dates",

limits=c(xMin, xMax),

breaks=myBreaks,

labels=myLabels) +

theme(axis.text.x=element_text(angle=-45, hjust = 0)) +

theme(legend.position="top")

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The second codes. (1 of 5)

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The second codes. (2 of 5)

rm(list=ls())

library(ggplot2)

library(reshape)

saveFileName

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The second codes. (3 of 5)

) +

theme(plot.title=element_text(hjust = 0.5)) +

theme(plot.title=element_text(colour = "blue")) +

theme(plot.subtitle=element_text(hjust = 0.5)) +

theme(plot.subtitle=element_text(colour = "black")) +

theme(plot.caption=element_text(hjust = 0.0)) +

theme(plot.caption=element_text(colour = "red")) +

theme(legend.title.align=0.5) +

theme(axis.text.x=element_text(angle=0, hjust = 0))

g + geom_line(aes(y=value, color=variable))

data_temp

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The second codes. (4 of 5)

}

g

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The second codes. (5 of 5)

theme(axis.text.x=element_text(angle=0, hjust = 0))

g + geom_line(aes(y=percentChange, color=variable))

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Hands-on exercises

1 In the first set of slides, your supervisor wants number ofchanges:

1 Because there are a lot of data points, and the data is “jaggy”a “smoothing” line might help tell a better story.

2 Change the order of the legend labels to alphabetic, and thecolors to the official colors of Christopher Newport University(http://cnu.edu/ocpr/styleguide/)

2 In the second set of slides:1 Your supervisor wants the labels in the legend to be clearer.2 Your supervisor wants the colors to be red and blue.

http://cnu.edu/ocpr/styleguide/

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Q & A time.

Q: Why is it that the moreaccuracy you demand from aninterpolation function, the moreexpensive it becomes tocompute?A: That’s the Law of SplineDemand.

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What have we covered?

Line charts with few items are:

Useful to show qualitative andquantitative changes in the“response” variable.Line attributes (color, width,dash-type) can be used todistinguish one line from another.X and Y axis can be linear ornon-linear

Maybe the most common type ofgraph

Next: Comparing a few categories across a few periods.

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References (1 of 1)

[1] Fed. Res. Bank Staff,About Economic Research at the St. Louis Fed,https://research.stlouisfed.org/about.html, 2018.

[2] Robert L. Harris,Information Graphics: A Comprehensive Illustrated Reference,Oxford University Press, 2000.

[3] Va. DEQ Staff, Groundwater Level Monitoring,https://www.deq.virginia.gov/Programs/Water/

WaterSupplyWaterQuantity/Drought/

DroughtIndicatorsandRegions/GroundwaterLevels.

aspx, 2018.

https://research.stlouisfed.org/about.htmlhttps://www.deq.virginia.gov/Programs/Water/WaterSupplyWaterQuantity/Drought/DroughtIndicatorsandRegions/GroundwaterLevels.aspxhttps://www.deq.virginia.gov/Programs/Water/WaterSupplyWaterQuantity/Drought/DroughtIndicatorsandRegions/GroundwaterLevels.aspxhttps://www.deq.virginia.gov/Programs/Water/WaterSupplyWaterQuantity/Drought/DroughtIndicatorsandRegions/GroundwaterLevels.aspxhttps://www.deq.virginia.gov/Programs/Water/WaterSupplyWaterQuantity/Drought/DroughtIndicatorsandRegions/GroundwaterLevels.aspx

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Files of interest

1 Code snippet to createimages in this presentation

2 Extract water levels script

3 Extract Federal Reserve

economic data

## First codesrm(list=ls())

library(ggplot2)

saveFileName