Question 1 Create a table called bpop that has two columns labeled time and

Question 1 create a table called bpop that has two

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Question 1. Create a table called b_pop that has two columns labeled time and population_total . The first column should contain the years from 1970 through 2015 (includ- ing both 1970 and 2015) and the second should contain the population of Bangladesh in each of those years. In [107]: b_pop = population . where( ' geo ' , are . equal_to( ' bgd ' )) . where( ' time ' , are . above_or_equal b_pop Out[107]: time | population_total 1970 | 65048701 1971 | 66417450 1972 | 67578486 1973 | 68658472 1974 | 69837960 1975 | 71247153 1976 | 72930206 1977 | 74848466 1978 | 76948378 1979 | 79141947 ... (36 rows omitted) In [108]: _ = ok . grade( ' q1_1 ' ) ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ Running tests --------------------------------------------------------------------- Test summary Passed: 3 Failed: 0 [ooooooooook] 100.0% passed 3
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Run the following cell to create a table called b_five that has the population of Bangladesh every five years. At a glance, it appears that the population of Bangladesh has been growing quickly indeed! In [109]: b_pop . set_format( ' population_total ' , NumberFormatter) fives = np . arange( 1970 , 2016 , 5 ) # 1970, 1975, 1980, ... b_five = b_pop . sort( ' time ' ) . where( ' time ' , are . contained_in(fives)) b_five Out[109]: time | population_total 1970 | 65,048,701 1975 | 71,247,153 1980 | 81,364,176 1985 | 93,015,182 1990 | 105,983,136 1995 | 118,427,768 2000 | 131,280,739 2005 | 142,929,979 2010 | 151,616,777 2015 | 160,995,642 Question 2. Create a table called b_five_growth that includes three columns, time , population_total , and annual_growth . There should be one row for every five years from 1970 through 2010 (but not 2015). The first two columns are the same as b_five . The third column is the annual growth rate for each five-year period. For example, the annual growth rate for 1975 is the yearly exponential growth rate that describes the total growth from 1975 to 1980 when applied 5 times. (Consult the Growth Rates example in the textbook to help understand how to compute the annual growth rate) Hint : Only your b_five_growth table will be scored for correctness; the other names are sug- gestions that you are welcome to use, change, or delete. Hint : You may find the exclude method to be helpful ( Docs ). In [110]: b_1970_through_2010 = b_five . exclude( -1 ) initial = b_1970_through_2010 . column( 1 ) changed = b_five . exclude( 0 ) . column( 1 ) b_five_growth = b_1970_through_2010 . with_column( ' annual_growth ' , ((changed / initial) ** b_five_growth . set_format( ' annual_growth ' , PercentFormatter) Out[110]: time | population_total | annual_growth 1970 | 65,048,701 | 1.84% 1975 | 71,247,153 | 2.69% 1980 | 81,364,176 | 2.71% 1985 | 93,015,182 | 2.64% 1990 | 105,983,136 | 2.25% 1995 | 118,427,768 | 2.08% 2000 | 131,280,739 | 1.71% 2005 | 142,929,979 | 1.19% 2010 | 151,616,777 | 1.21% 4
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In [111]: _ = ok . grade( ' q1_2 ' ) ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ Running tests --------------------------------------------------------------------- Test summary Passed: 4 Failed: 0 [ooooooooook] 100.0% passed While the population has grown every five years since 1970, the annual growth rate decreased dramatically from 1985 to 2005. Let’s look at some other information in order to develop a possible explanation. Run the next cell to load three additional tables of measurements about countries over time. In [112]: life_expectancy = Table . read_table( ' life_expectancy.csv ' ) child_mortality = Table . read_table( ' child_mortality.csv ' ) . relabeled( 2 , ' child_mortali fertility = Table . read_table( ' fertility.csv ' ) In [113]: life_expectancy Out[113]: geo | time | life_expectancy_years afg | 1800 | 28.21 afg | 1801 | 28.2 afg | 1802 | 28.19 afg | 1803 | 28.18 afg | 1804 | 28.17 afg | 1805 | 28.16 afg | 1806 | 28.15 afg | 1807 | 28.14 afg | 1808 | 28.13 afg | 1809 | 28.12 ... (43847 rows omitted) The life_expectancy table contains a statistic that is often used to measure how long people live, called life expectancy at birth . This number, for a country in a given year, does not measure how long babies born in that year are expected to live . Instead, it measures how long someone would live, on average, if the mortality conditions in that year persisted throughout their lifetime.
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