77 lines
2.5 KiB
Plaintext
77 lines
2.5 KiB
Plaintext
--- Salary ---
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1n9lRY5NxHjmXfqZfXJxytBqznzP_vWOPfSbv2rL-T38/Form Responses 1
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--- by_language ---
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SELECT PRIMARY_LANGUAGE_TECHNOLOGY_STACK AS LANGUAGE, COUNT(*) as tot,
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AVG(HOW_MANY_YEARS_HAVE_YOU_WORKED_IN_TECH) as YEARSWORKED,
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MIN(HOW_MANY_YEARS_HAVE_YOU_WORKED_IN_TECH) as yearsworked_min,
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MAX(HOW_MANY_YEARS_HAVE_YOU_WORKED_IN_TECH) as yearsworked_max,
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AVG(WHAT_IS_YOUR_ANNUALIZED_BASE_SALARY_IN_USD) as salary
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FROM salaries
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GROUP BY PRIMARY_LANGUAGE_TECHNOLOGY_STACK
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HAVING tot > 2;
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--- group by race_ethnicity ---
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= 'Other Race/ Ethnicity' or race_ethnicity = 'Black Non-Hispanic' or race_ethnicity = 'White Non-Hispanic' or race_ethnicity = 'Hispanic' or race_ethnicity = 'Asian and Pacific Islander'or race_ethnicity = 'Not Stated/Unknown'
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SELECT year,
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SUM( CASE WHEN race_ethnicity = 'Other Race/ Ethnicity' THEN deaths ELSE 0 END ) as Other,
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SUM( CASE WHEN race_ethnicity = 'Black Non-Hispanic' THEN deaths ELSE 0 END ) as Black_NH,
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SUM( CASE WHEN race_ethnicity = 'White Non-Hispanic' THEN deaths ELSE 0 END ) as White_NH,
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SUM( CASE WHEN race_ethnicity = 'Hispanic' THEN deaths ELSE 0 END ) as Hispanic,
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SUM( CASE WHEN race_ethnicity = 'Asian and Pacific Islander' THEN deaths ELSE 0 END ) as Asian_Pacific,
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SUM( CASE WHEN race_ethnicity = 'Not Stated/Unknown' THEN deaths ELSE 0 END ) as Unknown_Ethnicity
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FROM causes GROUP BY year
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--- # Import matplotlib, generate a plot, and output it.
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import matplotlib
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import matplotlib.pyplot as plt
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import io
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#switch to non display backend
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plt.switch_backend('agg')
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import numpy as np
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# Get object for dataset with given name.
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ds = vizierdb.get_dataset('causes')
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data = dict()
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for row in ds.rows:
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year = row.get_value('YEAR')
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ethnicity = row.get_value('RACE_ETHNICITY')
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deaths = row.get_value('DEATHS')
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if deaths != None:
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if ethnicity not in data:
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data[ethnicity] = dict()
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if year not in data[ethnicity]:
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data[ethnicity][year] = 0
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data[ethnicity][year] += deaths
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# Data for plotting
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fig, ax = plt.subplots()
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for ethnicity in data:
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by_year = data[ethnicity]
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years = sorted(by_year.keys())
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ax.plot(
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years,
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[ by_year[year] for year in years ],
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label = ethnicity,
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linewidth=3
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)
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ax.plot()
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ax.set(xlabel='Year', ylabel='Death Rate')
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ax.grid()
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ax.legend(loc = 'upper left')
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with io.BytesIO() as imgbytes:
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fig.savefig(imgbytes, format="svg")
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print(imgbytes.getvalue().decode("utf-8"))
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