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############# Module 5, Basics of data visualization ##############
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### EXCERCISES (Lessons 8 and 9)

# 1) Upload the data "island_soil_data_raw.csv" located in the "data" folder and explore the data a bit:


# 2) Make a simple scatterplot of of the relationship between Clay_perc and Sand_perc:


# 3) Now clean up this plot to make it look nice by adjusting the axis names, making the points larger
# and filled in, and any other adjustments you'd like to make to increase the visual appeal and
# presentability of this figure:


# 4) Upload the data "island_spatial_data_raw.csv" located in the "data" folder and explore the data a bit.
# View histograms of the the continuous variables in this new dataframe.


# 5) Now add the two new columns of spatial data to our other dataframe of soil data.
# Hint, make sure that both dataframes are ordered by island to ensure that 
# the new columns you add are in the right order.


# 6) View a histogram of island areas to see if there is a good cutoff 
# between larger and smaller islands:


# 7) It's difficult to tell from the histogram and since we only have
# 20 islands, just sort and then plot island area as a function of 1 to show them all


# 8) Do the same for island distance (isolation from the mainland shorline)


# 9) Add a new column indicating large islands as all with an area greater than 0.65 ha,
# and a new column indicating far islands as all with a distance greater than 350 m


# 10) Does there appear to be a difference in soil Clay percent between small and large islands?
# Use everything you know so far to visualize these questions and create presentable figures
# using both scatter and boxplots:


# 11) Now save these plots.


# That's it!

