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Explore_Weather_Trends

Explore-Weather-Trends-Udacity-Data-Analysis-Nanodegree

Exploring Weather Trends - Project Instructions

Summary In this project, you will analyze local and global temperature data and compare the temperature trends where you live to overall global temperature trends.

I. Steps taken to extract the data from SQL to be visualized in Excel:

  1. Tools: Sql (Udacity Workspace version)
  2. SELECT city FROM city_list WHERE country = 'Chile' SELECT year, city, country, avg_temp FROM city_data WHERE city = 'Los Angeles' AND country = 'Chile' SELECT avg_temp, year FROM global_data
  3. Downloaded and saved it as Avg_temp_Los_Angeles_1855_2013.csv
  4. Downloaded and saved it as Avg_temp_world_1750_2015.csv
  5. Changed format from CSV to .xlsx of files; open both files.
  6. Create two new columns world_five_year_mavg_temp (column C) and los_angeles_five_year_mavg_temp (column E)
  7. Switching all the commas into dots, in order to avoid the zero division error.
  8. Calculating the moving averages: Type in C6 =AVERAGE(B2 : B6); moving average from 1750 to 2015. Drag down the formula until the end of the data.
  9. Calculating the moving averages: Type in E111 AVERAGE(D107:D111); moving averages from 1850 to 2013. Drag down the formula until the end of the data.
  10. Line Chart: Creating a line chart by selecting the data and formatting it.
  11. Key considerations:
  • Chilean city Los Angeles has been selected because this city is the closest big city to where I live; Santiago, Chile.
  • Moving averages have been computed based on a 5-yr convention; the five-year interval was selected because it smooths data out, while at the same time it keeps peaks and trends somewhat close to the original data. Compared to the 2-yr and the 10-yr moving averages, the 5-ys moving average provides a good balance between asymmetry and silkiness of the data.
  • Since the data-set from Los Angeles starts in year 1850, this year has been selected as the starting point, even though the Global data-set begins in 1750.
  • The Data set from Los Angeles only reaches up until 2013; however, year 2015 has been set as the ending point, because it corresponds with Global data-set ending year.
  • Smoothed values have been computed from the fifth year on; that is why transparent lines and solid lines do not start at the same point.

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