Final (Part Two)

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Second Data Vizualization/Story

The story behind the second data visualization for the slave salves data set is that as the civil war was on the horizon, slavery grew for various reasons. The civil war wouldn’t have come into play if the southern states that seceded weren’t economically stable on their own. This is a consequence of the growth of slavery. Though the slave trade ended by the time the spike in slave sales occurred, slave records continued to increase in number. Why, you might ask? The international slave trade wasn’t in use anymore, but slaves were still in high demand because of the lucrative cotton kingdom.  Northern states slowly illegalized slavery while southern states continued to collect capital from the institution.

In the 1800’s, more slaves states were admitted into the union, maintaining the balance between free and slave states which makes sense of the rise in the amount of slave records as legislations regarding slavery were passed.

Slave records also increased because slave labor became more profitable as a result of the cotton gin’s invention at the end of the 1700’s and it’s widespread use during the 1800’s. The cotton kingdom was the cash crop that emerged after tobacco crops started to dim in value. Cotton was not only valuable to southern states because it could be produced and in turn sold faster, but because European countries valued it too. Cotton was needed in countries such as Great Britain –since major countries depended on southern states they met the demand through buying more slaves (Quizlet).  This is another reason that the south was not hesitant to secede from the union –they had connections with countries on other continents because they had business affairs with them beforehand. Not only did the south have its own connection internationally apart from the northern part of the union, the cotton kingdom mad it so that the south was also economically viable on its own –southern states didn’t depend on northern action to make the bulk of their profit.

The main point behind this visualization is that slavery was common in southern states, but it grew drastically as the latter half of the 19th century started and progressed as circumstances nationwide changed, as did international demands on the south of the union.

 

Bibliography

“Quizlet QWait(‘dom’,function(){document.getElementById(‘PrintLogo’).setAttribute(‘src’,”https://quizlet.com/a/i/global/logo_print.du83.png”)});.” History Unit Two Flashcards. Accessed May 12, 2016. https://quizlet.com/14327446/history-unit-two-flash-cards/.

 

Process Documentation

Naturally, people are visual beings. Even if something tastes good, a person wouldn’t be likely to explore it if it’s not appealing to the eye. For this reason, chefs pride themselves on presentation –once our eyes see something good, we assume that it is good and vice versa. If people didn’t see what went on in concentration camps during the holocaust, they might not have believed its severity. All of the above examples and analogies provide a peek into the reasoning for the visual choices that I made regarding my first data visualization.

In class, we saw a visualization that used color and inversion to portray Iraq death tolls (if I’m not mistaken). These tools made the death tolls come alive without even having to look at the numbers. Such a visualization played a major part in this visualization of the slave sales data set. Though there are several visual interpretations of the same data set, the data being portrayed can vary extensively.

For this visualization, I saw the stacked timeline format as best for what I wanted to portray. I wanted to portray the growth of slavery in the states over time, and the stacking method shows the states more so as a unit. Meanwhile, the states having different colors still allows viewers to distinguish between the states in the dataset.

I chose to evaluate slave sales over time in this visualization because I wanted to make sure that even though I was using one data set to make two visualization, both visualizations were unique. In my eyes, slavery is such a broad topic that can be stretched to fit into almost any area of American history. Cotton production played a part in both of my arguments, but they revealed different things. I made this plain not only verbally, but visually. The stacked timeline literally appears as a growth at first sight and thus, the main point comes across. In addition, the visual appeal also manages to dramatize the 1800’s as a period during which slaves were in high demand. Throughout most of the graph, there is consistently a higher than normal amount of slave records that we see through spikes in the visualization.

Another part of my reasoning for choosing this type of visualization was that when I tried the bar graph form, neither my story nor my argument came across. If they didn’t come across to me clearly, viewers wouldn’t remotely grasp the idea behind the visualization. The collection of small bars representing each record that was entered showed how many records were entered in different time periods, but the stacked graph boldly illustrated the variance or lack thereof in slave records that were entered.

All in all, my final visualization came together seamlessly, especially with Professor Kane’s assistance. The bright colors draw viewers’ attention and the variations in color from state to state help readers to make sense of what each states records of slaves was from year to year within the time span of a century.

 

Argument

The institution of slavery in the United States was in place for almost 250 years. However, slavery seems more popular as the slave sales data set progresses in sequence (PBS, 2004). With peaks in slave records from 1770-1870, slavery in southern states seems to have grown as years went on, with its highest cumulative peak being in 1859. However, why were slave records so inconsistent? This is the question that will be answered through the evaluation of historical circumstances surrounding the 100 years between 1770 and 1870.

In the 1770’s there was a push for the liberation of slaves. In 1773, slaves in Massachusetts petitioned for their liberty and were not successful. By the end of 1774, the First Continental Congress decided to discontinue the slave trade and Virginia also took action against the importation of slaves. Georgia did the same in 1775, and the first abolition society was founded in Pennsylvania. However, by the next year the slave population in the colonies continued to grow. In 1820, Missouri was admitted as a slave state through the Missouri .Compromise (Educational Broadcasting Corporation, 2004). The growth of slavery in the 1800’s can also be attributed in part to the Louisiana Purchase that doubled the size of the United States territory (Rapid Growth of Slavery).

The cotton gin’s invention towards the end of the 1700’s also led to a burst in the demand for slaves in the south. Slaves were now able to produce cotton at a much higher rate which meant that masters could make more capital in a shorter span of time, and clearly they took advantage of such an opportunity (Rapid Growth of Slavery). As the 1800’s progressed, so did the causational relationship between the amount of cotton produced, and the number of slaves in the cotton producing United States. As the number of slaves grew, so did the amount of cotton in the U.S. Consequently, plantation income increased as well (8-1 Chains, 2010). The data visualization shows this relationship in its entirety. As the years go on, the amount of slave records increase first in smaller increments, and then they drastically increase by the late 1850’s.

Though Louisiana has one of the most presently large clusters of slave records, before 1840 Maryland had the highest amount of slaves in comparison to the other states. Before the cotton gin became a major factor, tobacco was a cash crop. Tobacco was lucrative in relation to European markets and Maryland was one of the epicenters of its production. However, as more northern states abolished slavery, tobacco production came to a low and the future of slavery was uncertain (Dodson, 2010).

The United States’ economy depended on slavery, and the economy shifted upwards or downwards depending on what and how much slaves produced. When the cotton industry was revolutionized by the cotton gin, the country had no choice but to shift in that direction because it was economically savvy. On another note, the economic benefits of slavery was a driving force behind how the confederate states could even be sustainable on their own.

 

 Bibliography

Corporation, Educational Broadcasting. “Slavery and the Making of America -Time and Place.” PBS. 2004. Accessed May 12, 2016. http://www.pbs.org/wnet/slavery/timeline/1773.html.

Corporation, Educational Broadcasting. PBS. 2004. Accessed May 12, 2016. http://www.pbs.org/wnet/slavery/teachers/lesson1c.html.

Dodson, Howard. “How Slavery Helped Build a World Economy.” National Geographic. October 28, 2010. Accessed May 12, 2016. http://news.nationalgeographic.com/news/2003/01/0131_030203_jubilee2_2.html.

“The Growth of Slavery in the 1800’s.” 8-1Chains -. January 12, 2010. Accessed May 12, 2016. https://8-1chains.wikispaces.com/The Growth of Slavery in the 1800’s.

“Rapid Growth of Slavery in the 1800’s.” Frederick Douglass Heritage. Accessed May 12, 2016. http://www.frederick-douglass-heritage.org/slavery-1800s/

 

 

 

 

Final (Part One)

Dataset Description
The dataset that I’ve chosen to analyze and evaluate is entitled “Slave Sales 1775-1865”. It includes geographic, time range, as well as numeric data. The geographic data that the slave sales dataset includes is the location from which the slaves’ information was recorded –Chatham, Georgia. The better part of slave sales consists of numerical data, but there is some revealing textual data. The columns are labeled date entry (anywhere from 1790’s to about 1863), sex, age in years, age in months, appraised (the price they can be sold for), skills, and defects. One of the most revealing/astonishing columns is the defects column. The simple use of the word defect reveals how the person that recorded this data set feels about and views slaves. Defect is a word use in the context of things being made in a massive quantity in which one of them has a glitch that affects their function, for example. People are not things that are produced in mass quantities that are classified as normal or not, but the general mentality at this point (geographically and sequentially) in history is revealed simple by the title of this column. If a slave master of another white person had a hernia which was considered a defect of slaves, they’d be considered ill, or otherwise because they were classified as what they are –people and not objects, or property. The numbers describe the ages and prices of male and female slaves. Whereas, the text describes what skills some slaves had, and on the other hand, what “defects” slaves had. These rows directly describe slaves in the year range of 1775-1865. The ages of these slaves range from birth/a few months old to about 79 years old or so. Slave masters probably didn’t figure to place senior citizens in the market for slave trade after a certain age, because input into keeping the person alive most likely is more or equal to the output they’d receive from them.
The data presented in Slave Sales 1175-1865 are all related. For example, males are priced higher than females. Males usually have more years in which they can work before their bodies start to decline, and they ate not restricted to just one type of work. In addition, males are best at things that bring in the most revenue –such as field work, for example. A woman’s body declines quicker than a man’s body. In addition, there may be a few days in which a woman can’t work because of child bearing. Women may not work as long hours as men because they’re the ones that cook for their families. In another sense, both women and men that are “in their prime” so to speak are also worth more. For example, a female slave age sixty is worth $50, while a female that is sixteen years old is worth $500, as is a 30 year old woman. A woman that is 60 years old is post-menopausal most likely, can’t breastfeed, and has fragile bones, among other things. Surprisingly, the 16 year old and 30 year old are worth exactly the same and neither has any skills or defects listed. Both of these women, and women in their age range in general are of age to be child-bearers, which slave masters may see as a skill. In terms of slavery, child bearing brings forth more slaves and in some instances, children from the slave master. Slave masters can also add these women to their list of mistresses. Women that are of age to have children age are most likely expected to breastfeed the slave masters children as well. These abilities are exclusive to women of age to bear children. Therefore, these women are worth more monetarily.
A man that is 50 years old with no defects or skills is also priced highly (generally speaking) at around $550 –more than a woman that is in her prime. Men are probably more valuable to slave owners because they can produce the higher amounts of product for longer periods of time because of their stamina. A 50 year old slave in 1848 is probably a lot or active than your average 50 year old today. These men can still have children with younger women (increasing the slave population) and do field work for most of their lives. They serve a dual purpose for a longer period of time. Historically, at that point in time the 50 year old could have very well been born into slavery and as a result is accustomed to slave labor, its excruciating pain, extended hours, and mental and physical abuse.

Data Visualization/Story

The visual data that I chose to use to describe the slave sales data set is a graph. Graphs with entities separated by color are more appealing to a person’s eye in general, and their mind automatically notices the difference in volume of each color, or lack thereof. For example, if a person sees a pie chart that is 75 percent red and the remainder is green, they’ll automatically wonder what the red area represents and why it’s so plentiful. On the other hand, colors in bar graphs create distinctions, but the length of the bars is what tells all. Where the z-axis is placed (on the bottom, side, or top of the graph) also has an impact on what viewers’ perception. An x-axis that’s on top as oppose to on the bottom typically has an adverse effect at the first glance compared to if it was on the bottom because it looks as if numbers are decreasing as the bars decrease in length.
I chose the bar graph lay out because it makes it seem as if certain states were forging ahead of others. Essentially, leaving them in the dust of the money they spent on slaves. This scale isn’t the typical graph, but I do think that it gets the point across visually without having to see the prior spread sheet to analyze the data. I chose the deep burgundy color because it wasn’t alarmingly red, but the burgundy resembles blood and this tugs on views heart strings –especially in the context of slave sales.
The context surrounding the slave sales data set is the rise of the cotton kingdom. The spike in Louisiana slave purchases may be due to the expansion of slavery and cotton production, which makes sense. The raw data set itself shows that men in their prime are bought for higher prices (keep in mind that man’s prime is longer than a woman’s). Women, on the other hand, are of more value when they are of age to bear children and their value probably depreciates so in a time when the goal is to increase production, men are probably the more ideal choice. Though child bearing and reproduction is important, this timeline probably seems longer to a person that wants to capitalize off of cotton production high while it’s hot –wait nine to ten months for a mother to give birth and a few more years for that baby to be mature enough to pick cotton themselves. Women were still being bought at an increasing rate, while men, as we see in Louisiana, were in higher demand.
In terms of sequence, the range of the slave sales data set covers the rise of the cotton kingdom which was vaguely 1830-1861. Therefore, the increase in millions spent by the states is associated with the rise in cotton demand. Aside from natural reasons, the cotton revolution is the main reason that states in that time period spent hundred off dollars to buy quality slaves because they’d prove vital in capitalizing off of the cotton kingdom.

First Visualization Process Documentation
The first visualization that I created to represent the slave sales data set described the amount of females versus males that southern states purchased in the approximately 100 year time frame that the data covered. My choices in color and design reflected what I aimed for the visualization to portray.
In terms of my color choices, I used a deep red color because slavery in the U.S. wasn’t a cheerful time for African Americans, and its main purpose was to highlight how states valued specifically male and female slaves. In class, I saw another graph that used inversion to portray the creator’s point of view on the data –death tools in Iraq. This tactic caught my eye because the creator didn’t change the data, they changed the way it was presented. Though I didn’t use inversion, I rotated the bar graph so that the bars stemmed from the left side as oppose to growing from the bottom as in conventional bar graphs. With this format, it looks as if the bars are racing each other in a sense, and Louisiana is surpassing them all.
I chose to compare how the states valued males versus females to expound upon a broader idea –male slaves often had higher value from a slaver master’s perspective. Through my research that is expounded upon in my argument, gender wasn’t the only thing that effected a slave’s appraised value –age played a part as well. Young women that of age to bear children were valued as high as men in their physical prime.
A slave’s value wasn’t only what they were worth at the time, but what services they could provide for the slave master in the long run. For example, a 19 year old man would be valued more than a 19 year old woman because after the young woman’s child bearing years are over, her value decreases. On the other hand, a man’s body had more longevity in terms of field work and things of that nature that were of value to slave owners. This was displayed through the bar graph because all of bars representing the sum each state spent on either gender were higher for males. Slave masters made an investment in both male and female slaves because of obvious reasons such a reproduction, but females also has value outside of child bearing. Women often worked inside of the slave masters homes tending to his children in addition to her own children, cooking, cleaning, and things of the like. Slave masters also took female slaves as their concubines to satisfy their sexual desires.
All in all, this visualization for the slave sales data set provides a stepping stone for all that my argument encompasses. The position of the bars gives readers insight into my argument because males are clearly valued more than females, but women don’t fall too far behind men for most states except for Louisiana. Viewers see that Louisiana doesn’t follow the common trend and it leaves them wondering why that is so.

Bibliography
“Quizlet QWait(‘dom’,function(){document.getElementById(‘PrintLogo’).setAttribute(‘src’,”https://quizlet.com/a/i/global/logo_print.du83.png”)});.” History Unit Two Flashcards. Accessed May 12, 2016. https://quizlet.com/14327446/history-unit-two-flash-cards/.

Slavery –the practice or system of owning slaves (Random House Inc., 2016). Such a system served as a pillar of the U.S. economy and social structure. By 1850, slaves in the U.S. were worth 1.3 billion dollars. Or in other words, American slaves were worth one fifth of the entire nation’s wealth (Goyette, 2014). Such information makes sense of the data that is displayed in the slave sales data set. It’s easy for people to think about how rich America’s history is, but how often do these people think about the hands that made it great? From the Caribbean to the mainland slaves hands were goldmines. Cotton wouldn’t have boomed without people to grow, harvest, and pick it. Tobacco would be a delicacy if lives weren’t stolen and then bought in order to harvest it. These statements ring true for many of the goods produced by slaves. This may be contrary to popular belief, but the American Economy must have depended on slavery for the better part of its history before the start of the 20th century. As a result, slaves were in high demand. But the question is –which slaves were in high demand and why?
According to measuring worth, a slave’s value was truly the value of the how much they’re expected to produce (Williamson and Cain, 2011). In other words the value of a slave was not really the slave’s value per say, but the value of the service that they could provide. For example, an elderly woman wouldn’t be expected to produce much, especially if she has any outstanding physical condition (or “defects”) such a missing finger or cataracts. As we see in this data visualization, males were clearly expected to produce more because generally, more money was spent on males. In Louisiana, males that were between the ages of 15 and 44 had the highest values and men within the 24-35 age-range held the peak values. As for females, those in the approximate age range of 14-33 years old held the highest value. This is no surprise, since these are typically a female’s peak child-bearing years (Williamson and Cain, 2011). Slaves weren’t only valued for what they could produce in the fields, but for their skills as well. Premiums were paid for slaves that had artisan skills such as cooking, carpentry, and blacksmithing, among other domestic skills. On the other hand, a slave’s value was depleted if they had characteristics or deformities that would inhibit their production such as drinking, being crippled, or being a frequent runaway (Williamson and Cain, 2011).
The spreadsheet itself uses appraised values that are generally under one thousand dollars. However, if we were to convert these prices to what they’d be today, the average range for which a slave would be sold would be 12 thousand to 176 thousand dollars. In other words, a slave was worth anywhere between the price of buying a used car and a mortgage. For example, a slave that would be sold for $400 in 1850 would be worth about $82,000 today. (Williamson and Cain, 2011). For slave owners, perhaps foregoing purchasing a home or another luxury item was worth investing in a few decades worth of slave services that would have a major return in the long run.
Though all states in the slave sales data set purchased slaves to some degree, the massive amount of capital spent on both female and male slaves by Louisiana is strikingly higher than the other states. Louisiana was most likely subject to the other factors such as the cotton boom that justified the desire across the country for slaves in their prime. If this is the case, why was Louisiana so much more passionate (according the data visualization) in the buying of slaves? At the top of the 18th century, Louisiana was the resting ground for only ten people of color. However, the French imported about six thousand slaves in Louisiana (Whitney Plantation). After the Seven Years War that concluded in 1763, Louisiana was occupied partly by Britain and partly by Spain. Subsequently the territory was reopened to large scale imports of slaves. By 1795, about thirty years later, the amount of slaves ballooned to almost 20,000. A few years later in 1807, the Atlantic slave trade was prohibited. However, this didn’t stop those that were persistent about sustaining slavery. Thousands of slaves were smuggled into the territory from Africa and the Caribbean illegally in addition to the domestic slave trade in the upper southern part of the U.S. If we fast-forward towards the end of the data visualization in 1860, there were over three hundred thousand slaves in Louisiana and nearly 20,000 free people of color.
In the time period that the slave sales data set spanned, Louisiana had avid reasoning for demanding so much slave labor. While the territory was under French rule, the services that slaves provided varied and the territory was highly dependent on slave labor. Such tasks included cooking, hulling rice with mortars and pestles, carpentry, and raising cattle (oxen, sheep, cows, and poultry among other animals). Female slaves also took care of their master’s personal task of caring for their children. Though aiding in raising their children mad a masters life easier, the mass importation of slaves gave masters a new lease on life. Wealth was easily in a master’s reach with the slave trade (Whitney Plantation).
Coupled with indigo production, the mass importation of slaves gave masters a more prestigious standard of living. Another reason for Louisiana’s higher dispensed capital for slaves is indigo production under Spanish rule. Females were a main part in raising indigo crops and males extracted them –which makes sense of why the territory spend large amounts of capital on both females and males (Whitney Plantation).
Slaves were a part of American culture for centuries, and part of that time is covered in the slave sales data set. The U.S. depended on slaves for their free services in order to make capital. So much so, that they were willing to shell out what would now be thousands upon thousands of dollars on slave labor because of its returns. Where would the U.S. be on a global scale without slave labor? –A question that can answer itself.

Bibliography

Slavery. Dictionary.com. Dictionary.com Unabridged. Random House, Inc. http://www.dictionary.com/browse/slavery (accessed: April 25, 2016).

Goyette, Braden. “5 Things About Slavery You Probably Didn’t Learn In Social Studies: A Short Guide To ‘The Half Has Never Been Told'” The Huffington Post. October 23, 2014. Accessed April 26, 2016. http://www.huffingtonpost.com/2014/10/23/the-half-has-never-been-told_n_6036840.html.

Whitney Plantation. “Slavery In Louisiana.” Slavery In Louisiana. Accessed April 26, 2016. http://www.whitneyplantation.com/slavery-in-louisiana.html.

Williamson, Samuel H., and Louis P. Cain. “Measuring Worth – Measuring the Value of a Slave.” Measuring Worth – Measuring the Value of a Slave. 2011. Accessed April 26, 2016. https://www.measuringworth.com/slavery.php.

Argument for Visualization Number One

Slavery –the practice or system of owning slaves (Random House Inc., 2016). Such a system served as a pillar of the U.S. economy and social structure. By 1850, slaves in the U.S. were worth 1.3 billion dollars. Or in other words, American slaves were worth one fifth of the entire nation’s wealth (Goyette, 2014). Such information makes sense of the data that is displayed in the slave sales data set. It’s easy for people to think about how rich America’s history is, but how often do these people think about the hands that made it great? From the Caribbean to the mainland slaves hands were goldmines. Cotton wouldn’t have boomed without people to grow, harvest, and pick it. Tobacco would be a delicacy if lives weren’t stolen and then bought in order to harvest it. These statements ring true for many of the goods produced by slaves. This may be contrary to popular belief, but the American Economy must have depended on slavery for the better part of its history before the start of the 20th century. As a result, slaves were in high demand. But the question is –which slaves were in high demand and why?
According to measuring worth, a slave’s value was truly the value of the how much they’re expected to produce (Williamson and Cain, 2011). In other words the value of a slave was not really the slave’s value per say, but the value of the service that they could provide. For example, an elderly woman wouldn’t be expected to produce much, especially if she has any outstanding physical condition (or “defects”) such a missing finger or cataracts. As we see in this data visualization, males were clearly expected to produce more because generally, more money was spent on males. In Louisiana, males that were between the ages of 15 and 44 had the highest values and men within the 24-35 age-range held the peak values. As for females, those in the approximate age range of 14-33 years old held the highest value. This is no surprise, since these are typically a female’s peak child-bearing years (Williamson and Cain, 2011). Slaves weren’t only valued for what they could produce in the fields, but for their skills as well. Premiums were paid for slaves that had artisan skills such as cooking, carpentry, and blacksmithing, among other domestic skills. On the other hand, a slave’s value was depleted if they had characteristics or deformities that would inhibit their production such as drinking, being crippled, or being a frequent runaway (Williamson and Cain, 2011).
The spreadsheet itself uses appraised values that are generally under one thousand dollars. However, if we were to convert these prices to what they’d be today, the average range for which a slave would be sold would be 12 thousand to 176 thousand dollars. In other words, a slave was worth anywhere between the price of buying a used car and a mortgage. For example, a slave that would be sold for $400 in 1850 would be worth about $82,000 today. (Williamson and Cain, 2011). For slave owners, perhaps foregoing purchasing a home or another luxury item was worth investing in a few decades worth of slave services that would have a major return in the long run.
Though all states in the slave sales data set purchased slaves to some degree, the massive amount of capital spent on both female and male slaves by Louisiana is strikingly higher than the other states. Louisiana was most likely subject to the other factors such as the cotton boom that justified the desire across the country for slaves in their prime. If this is the case, why was Louisiana so much more passionate (according the data visualization) in the buying of slaves? At the top of the 18th century, Louisiana was the resting ground for only ten people of color. However, the French imported about six thousand slaves in Louisiana (Whitney Plantation). After the Seven Years War that concluded in 1763, Louisiana was occupied partly by Britain and partly by Spain. Subsequently the territory was reopened to large scale imports of slaves. By 1795, about thirty years later, the amount of slaves ballooned to almost 20,000. A few years later in 1807, the Atlantic slave trade was prohibited. However, this didn’t stop those that were persistent about sustaining slavery. Thousands of slaves were smuggled into the territory from Africa and the Caribbean illegally in addition to the domestic slave trade in the upper southern part of the U.S. If we fast-forward towards the end of the data visualization in 1860, there were over three hundred thousand slaves in Louisiana and nearly 20,000 free people of color.
In the time period that the slave sales data set spanned, Louisiana had avid reasoning for demanding so much slave labor. While the territory was under French rule, the services that slaves provided varied and the territory was highly dependent on slave labor. Such tasks included cooking, hulling rice with mortars and pestles, carpentry, and raising cattle (oxen, sheep, cows, and poultry among other animals). Female slaves also took care of their master’s personal task of caring for their children. Though aiding in raising their children mad a masters life easier, the mass importation of slaves gave masters a new lease on life. Wealth was easily in a master’s reach with the slave trade (Whitney Plantation).
Coupled with indigo production, the mass importation of slaves gave masters a more prestigious standard of living. Another reason for Louisiana’s higher dispensed capital for slaves is indigo production under Spanish rule. Females were a main part in raising indigo crops and males extracted them –which makes sense of why the territory spend large amounts of capital on both females and males (Whitney Plantation).
Slaves were a part of American culture for centuries, and part of that time is covered in the slave sales data set. The U.S. depended on slaves for their free services in order to make capital. So much so, that they were willing to shell out what would now be thousands upon thousands of dollars on slave labor because of its returns. Where would the U.S. be on a global scale without slave labor? –A question that can answer itself.

Bibliography

Slavery. Dictionary.com. Dictionary.com Unabridged. Random House, Inc. http://www.dictionary.com/browse/slavery (accessed: April 25, 2016).

Goyette, Braden. “5 Things About Slavery You Probably Didn’t Learn In Social Studies: A Short Guide To ‘The Half Has Never Been Told'” The Huffington Post. October 23, 2014. Accessed April 26, 2016. http://www.huffingtonpost.com/2014/10/23/the-half-has-never-been-told_n_6036840.html.

Whitney Plantation. “Slavery In Louisiana.” Slavery In Louisiana. Accessed April 26, 2016. http://www.whitneyplantation.com/slavery-in-louisiana.html.

Williamson, Samuel H., and Louis P. Cain. “Measuring Worth – Measuring the Value of a Slave.” Measuring Worth – Measuring the Value of a Slave. 2011. Accessed April 26, 2016. https://www.measuringworth.com/slavery.php.

Final Project Story Draft Due 4/14

The visual data that I chose to use to describe the slave sales data set is a graph. Graphs with entities separated by color are more appealing to a person’s eye in general, and their mind automatically notices the difference in volume of each color, or lack thereof. For example, if a person sees a pie chart that is 75 percent red and the remainder is green, they’ll automatically wonder what the red area represents and why it’s so plentiful. On the other hand, colors in bar graphs create distinctions, but the length of the bars is what tells all. Where the z-axis is placed (on the bottom, side, or top of the graph) also has an impact on what viewers’ perception. An x-axis that’s on top as oppose to on the bottom typically has an adverse effect at the first glance compared to if it was on the bottom because it looks as if numbers are decreasing as the bars decrease in length.
I chose the bar graph lay out because it makes it seem as if certain states were forging ahead of others. Essentially, leaving them in the dust of the money they spent on slaves. This scale isn’t the typical graph, but I do think that it gets the point across visually without having to see the prior spread sheet to analyze the data. I chose the deep burgundy color because it wasn’t alarmingly red, but the burgundy resembles blood and this tugs on views heart-strings –especially in the context of slave sales.
The context surrounding the slave sales data set is the rise of the cotton kingdom. The spike in Louisiana slave purchases may be due to the expansion of slavery and cotton production, which makes sense. The raw data set itself shows that men in their prime are bought for higher prices (keep in mind that man’s prime is longer than a woman’s). Women, on the other hand, are of more value when they are of age to bear children and their value probably deprecates so in a time when the goal is to increase production, men are probably the more ideal choice. Though child-bearing and reproduction is important, this timeline probably seems longer to a person that wants to capitalize off of cotton production high while it’s hot –wait nine to ten months for a mother to give birth and a few more years for that baby to be mature enough to pick cotton themselves. Women were still being bought at an increasing rate, while men, as we see in Louisiana, were in higher demand.
In terms of sequence, the range of the slave sales data set covers the rise of the cotton kingdom which was vaguely 1830-1861. Therefore, the increase in millions spent by the states is associated with the rise in cotton demand. Aside from natural reasons, the cotton revolution is the main reason that states in that time period spent hundred off dollars to buy quality slaves because they’d prove vital in capitalizing off of the cotton kingdom.

Pamela’ s Final Proposal

The first dataset that I’ve chosen to analyze and evaluate is entitled “Slave Sales 1775-1865”. It includes geographic, time range, as well as numeric data. The geographic data that the slave sales data set includes is the location from which the slaves’ information was recorded –Chatham, Georgia. The better part of slave sales consists of numerical data, but there is some revealing textual data. The columns are labeled date entry (anywhere from 1790’s to about 1863), sex, age in years, age in months, appraised (the price they can be sold for), skills, and defects. One of the most revealing/astonishing columns is the defects column. The simple use of the word defect reveals how the person that recorded this data set feels about and views slaves. Defect is a word use in the context of things being made in a massive quantity in which one of them has a glitch that affects their function, for example. People are not things that are produced in mass quantities that are classified as normal or not, but the general mentality at this point (geographically and sequentially) in history is revealed simple by the title of this column. If a slave master of another white person had a hernia which was considered a defect of slaves, they’d be considered ill, or otherwise because they were classified as what they are –people and not objects, or property. The numbers describe the ages and prices of male and female slaves. Whereas, the text describes what skills some slaves had, and on the other hand, what “defects” slaves had. These rows directly describe slaves in the year range of 1775-1865. The ages of these slaves range from birth/a few months old to about 79 years old or so. Slave masters probably didn’t figure to place senior citizens in the market for slave trade after a certain age, because input into keeping the person alive most likely is more or equal to the output they’d receive from them.
The data presented in Slave Sales 1175-1865 are all related. For example, males are priced higher than females. Males usually have more years in which they can work before their bodies start to decline, and they ate not restricted to just one type of work. In addition, males are best at things that bring in the most revenue –such as field work, for example. A woman’s body declines quicker than a man’s body. In addition, there may be a few days in which a woman can’t work because of child-bearing. Women may not work as long hours as men because they’re the ones that cook for their families. In another sense, both women and men that are “in their prime” so to speak are also worth more. For example, a female slave age sixty is worth $50, while a female that is sixteen years old is worth $500, as is a 30-year-old woman. A woman who is 60 years old is post-menopausal most likely, can’t breastfeed, and has fragile bones, among other things. Surprisingly, the 16-year-old and 30-year-old are worth exactly the same and neither has any skills or defects listed. Both of these women, and women in their age range in general are of age to be child-bearers, which slave masters may see as a skill. In terms of slavery, child-bearing brings forth more slaves and in some instances, children from the slave master. Slave masters can also add these women to their list of mistresses. Women that are of age to have children age are most likely expected to breastfeed the slave masters children as well. These abilities are exclusive to women of age to bear children. Therefore, these women are worth more monetarily.
A man who is 50 years old with no defects or skills is also priced highly (generally speaking) at around $550 –more than a woman who is in her prime. Men are probably more valuable to slave owners because they can produce the higher amounts of product for longer periods of time because of their stamina. A 50-year-old slave in 1848 is probably a lot or active than your average 50-year-old today. These men can still have children with younger women (increasing the slave population) and do field work for most of their lives. They serve a dual purpose for a longer period of time. Historically, at that point in time the 50-year-old could have very well been born into slavery and as a result is accustomed to slave labor, its excruciating pain, extended hours, and mental and physical abuse.

Data Visualization Readings and Analysis

(Mentioned in Post)

Each of the articles that I’ll be discussing are all connected by one thing –visual data. Since we’re in a digital history and class and most of us don’t have the longest attention spans –visualizing data can be an easy way out as oppose to looking at spreadsheets. However, is the grass really greener on the other side?
The main point in “How to Lie with Data Visualization” was that regardless of what the cold, hard numbers are, people and corporations can lie through the visuals associated with statistics –as its title insinuates. Though people are obligated to post the true statistics, they make negative statistics work in their favor through the way it is presented visually. For example, turning the y-axis on a graph upside down, making it seems as if numbers are decreasing while they’re doing no such thing –as in the gun control example. As a result of this tactic, it would seem that at a glance after Florida’s ’Stand Your Ground Law’, the amount of gun deaths plummeted dramatically. However, the exact opposite happened but in moving the y-axis the creators of this graph succeeded in deceiving viewers.
Ben Jones’ article (based on William Zinsser’s book) touches on 7 different points that concern non-fiction writing tips, as well as those regarding visual data. The first point that he makes regarding “The Transaction”. In other words, this is the reflection of how a creator of a visualization feels about the set of data onto the set of data itself. This was illustrated very vividly in the video included in the article. I found that the creator of this visualization is very focused on the impact of deaths as a result of guns. The creator didn’t use a conventional graph, but single, slim straw like curves so that the impact of the amount of gun deaths will truly be seen by its viewers. Not only are the amounts of gun deaths and age ranges made visual, but the years of those lives that were lost as well. This provides a different perspective as oppose to the conventional bar graph. That wouldn’t show how many years are lost in such deaths.
One of the most profound points made in the “On Visualizing Data Well” was exhibited in “How to Lie with Data Visualization”. According to Ben Jones, the humanity of the visualizer and their views are reflected in what they create. For example, in Ravi Parikh’s article, one of his examples included how people are deceived by bar graphs –such as the one attached displaying baseball stats. In this case, what John Theibault was saying regarding visualization is proven true: it’s used to quickly identify patterns in large datasets during the research process. However, what happens when data visualization is deceitful? According to Parikh, “We’re wired to misinterpret the data”. For example, in a deceitful pie chart with slices of 60%, 63% and 70%, clearly the person behind this data set used the wrong graph because these three amounts do not amount to 100% collectively. This makes viewers think that candidates (in this example) are closer or further in the race than they appear.

Why do you think some people/companies use deceitful visual data?
Would you rather to simply see statistics as oppose to visual data?
What are some examples of visual data that we see in every day culture? (Commercials, for example)

A Promenade down Pearl Street

I. The Hampton Inn and Suites has a relaxing environment equip with Wi-Fi for guests and is conveniently placed amidst the other points on this promenade down Pearl Street for tourists.
“Why Hampton?” Hampton by Hilton. Accessed March 03, 2016. http://hamptoninn3.hilton.com/en/about/why-hampton/index.html.

Built during the great depression, The Palace Theatre is one of the sole venues of its kind that is still active. Its stage is home to comics, musical acts, and other forms of entertainment.
“Welcome to the Palace Theatre | Albany NY.” Welcome to the Palace Theatre | Albany NY. Accessed March 03, 2016. http://palacealbany.com/.
The first church in Albany also has historical significance as the first church in the upstate area. It was founded in 1642 by Dutch settlers and in the 1700’s served as a hospital for soldiers during the battle of Saratoga.
“History.” The First Church in Albany. Accessed March 03, 2016. http://firstchurchinalbany.weebly.com/history.html.
The Pearl Street Pub is located in the entertainment district of downtown Albany. It’s economically priced, so those on this tour route may very well want to stop in and get a bite to eat.
“Mon – Fri: 11am – 4am Sat: 12pm – 4am | Sun: 11am – 8pm Kitchen Closes at 9pm.” The Pearl Street Pub & Dirty Martini Lounge. Accessed March 03, 2016. http://thepearlstreetpub.com/menu.asp.
The Times Union Center is a sports arena that hosts basketball games and features concession stands with and without alcohol.
“Events.” Timesunioncenter-albany.com. Accessed March 03, 2016. http://www.timesunioncenter-albany.com/events.
II. Google estimates that my tour will take about 15 minutes.
III. The central focus of my tour is “A Pearl Street Promenade” because it’s located in downtown Albany; a social center of sorts in this capital region. I know that many people are doing tours down State Street, so I figured that Pearl Street would be a nice change. The audience for this tour is a wide range of young adults. This tour also caters to groups of friends and couples that are visiting, since all of my locations are walking distance from the area’s hotel. The big take away point that those who take it should walk away with is that you can do more than you think without excessive travel. Collectively, my tour has a little something for everyone from the person that just likes to relax, to some one that enjoys more of the night scene, and even those that are self-proclaimed food fanatics. On the other hand, the Times Union Center is for sports fans and it gives visitors other options for entertainment .The Palace Theatre is classic, so it adds an element of historical significance to the tour and balances out the Times Union Center. The Hampton Inn is classy and it gives tourists a good balance between the more populated places on the tour such as the Pub and the Theatre since they’d be in their room at their own discretion. People can relax after seeing a show at the theatre, and unwind even more after going for drinks at the pub. The First Church in Albany is historic, scenic, and classic. This stop on the walking tour can bring those on the tour back to a simpler time and diversify the other locations along Pearl Street. Lastly, each of these locations is in close proximity to Pearl Palooza! –an annual music festival held on Pearl Street in the summer.
IV. https://upload.wikimedia.org/wikipedia/commons/b/be/First_Reformed_Church%2C_Albany.jpg
-This is a photo of the First Albany Church
http://palacealbany.com/images/events/lg/Seinfeld15.jpg
-This is a picture of Jerry Seinfeld, one of the acts set to take the stage at the Palace Theatre
V. What’s so great about the Pearl Street Pub?
Who are some of the most famous people that have headlined the palace theatre?
What could a single person do on this tour with a friend?

Fashion in Albany!

muhlfelders women's clothing store albany ny early 1900s

Fox shop  womens clothing store 1960s Albany NY

Flah's womens clothing store 1923 Albany NY (1920s)

Fashion in Albany can be quite a midterm project topic because Albany is known for its cold weather, so as historians we can see how that effected life in the 1900’s. We can also see what different staple locations in Albany contributed to the fashion culture and how different or similar the location is to serving the purpose that it once did.