Editing Community Data Science Course (Spring 2017)/Day 7 Exercise

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# Download the data from [http://proximityone.com/countytrends/cd11414dp3.csv here].
# Download the data from [http://proximityone.com/countytrends/cd11414dp3.csv here].
# Using the data description above, see if you can figure out which columns contain which rows in the raw data. Identify the columns for construction, manufacturing, and finance workforce. Also, identify columns for median and mean income.
# Using the data description above, see if you can figure out which columns contain which rows in the raw data. Identify the columns for construction, manufacturing, and finance workforce. Also, identify columns for median and mean income.
# Open the file in python, split each line, and read the fields you identified in step 2 into a list. This is a good source of help: [[Community_Data_Science_Course_(Spring_2017)/Day_4_Notes]]
# Open the file in python, split each line, and read the fields you identified in step 2 into a list.
This is a good source of help: [[Community_Data_Science_Course_(Spring_2017)/Day_4_Notes]]
# Remove Puerto Rico and Washington D.C.
# Remove Puerto Rico and Washington D.C.
# Compute the percent of workers in each of the industries above and add it to the list of data.
# Compute the percent of workers in each of the industries above and add it to the list of data.
# Output the data to a new CSV file. (add a header).
# Output the data to a new CSV file. (add a header).
# Open this data in Excel. Try to identify whether there is a relationship between percent of a district in each industry and median or mean salary.
# Open this data in Excel. Try to identify whether there is a relationship between percent of a district in each industry and median or mean salary.
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