Python Data Visualization Essentials Guide
For Exercises in Data Visualization
@kaggle.kalilurrahman_python_data_visualization_essentials_guide
For Exercises in Data Visualization
@kaggle.kalilurrahman_python_data_visualization_essentials_guide
CREATE TABLE n_1976_2020_president (
"year" BIGINT,
"state" VARCHAR,
"state_po" VARCHAR,
"state_fips" BIGINT,
"state_cen" BIGINT,
"state_ic" BIGINT,
"office" VARCHAR,
"candidate" VARCHAR,
"party_detailed" VARCHAR,
"writein" VARCHAR,
"candidatevotes" BIGINT,
"totalvotes" BIGINT,
"version" BIGINT,
"notes" VARCHAR,
"party_simplified" VARCHAR
);
CREATE TABLE n_19762016usprez (
"year" BIGINT,
"state" VARCHAR,
"state_po" VARCHAR,
"state_fips" BIGINT,
"state_cen" BIGINT,
"state_ic" BIGINT,
"office" VARCHAR,
"candidate" VARCHAR,
"party" VARCHAR,
"writein" BOOLEAN,
"candidatevotes" BIGINT,
"totalvotes" BIGINT,
"version" BIGINT,
"notes" VARCHAR
);
CREATE TABLE n_2015 (
"country" VARCHAR,
"region" VARCHAR,
"happiness_rank" BIGINT,
"happiness_score" DOUBLE,
"standard_error" DOUBLE,
"economy_gdp_per_capita" DOUBLE,
"family" DOUBLE,
"health_life_expectancy" DOUBLE,
"freedom" DOUBLE,
"trust_government_corruption" DOUBLE,
"generosity" DOUBLE,
"dystopia_residual" DOUBLE
);
CREATE TABLE n_2016 (
"country" VARCHAR,
"region" VARCHAR,
"happiness_rank" BIGINT,
"happiness_score" DOUBLE,
"lower_confidence_interval" DOUBLE,
"upper_confidence_interval" DOUBLE,
"economy_gdp_per_capita" DOUBLE,
"family" DOUBLE,
"health_life_expectancy" DOUBLE,
"freedom" DOUBLE,
"trust_government_corruption" DOUBLE,
"generosity" DOUBLE,
"dystopia_residual" DOUBLE
);
CREATE TABLE n_2017 (
"country" VARCHAR,
"happiness_rank" BIGINT,
"happiness_score" DOUBLE,
"whisker_high" DOUBLE,
"whisker_low" DOUBLE,
"economy_gdp_per_capita" DOUBLE,
"family" DOUBLE,
"health_life_expectancy" DOUBLE,
"freedom" DOUBLE,
"generosity" DOUBLE,
"trust_government_corruption" DOUBLE,
"dystopia_residual" DOUBLE
);
CREATE TABLE n_2018 (
"overall_rank" BIGINT,
"country_or_region" VARCHAR,
"score" DOUBLE,
"gdp_per_capita" DOUBLE,
"social_support" DOUBLE,
"healthy_life_expectancy" DOUBLE,
"freedom_to_make_life_choices" DOUBLE,
"generosity" DOUBLE,
"perceptions_of_corruption" DOUBLE
);
CREATE TABLE n_2019 (
"overall_rank" BIGINT,
"country_or_region" VARCHAR,
"score" DOUBLE,
"gdp_per_capita" DOUBLE,
"social_support" DOUBLE,
"healthy_life_expectancy" DOUBLE,
"freedom_to_make_life_choices" DOUBLE,
"generosity" DOUBLE,
"perceptions_of_corruption" DOUBLE
);
CREATE TABLE aapl (
"date" TIMESTAMP,
"open" DOUBLE,
"high" DOUBLE,
"low" DOUBLE,
"close" DOUBLE,
"adj_close" DOUBLE,
"volume" BIGINT
);
CREATE TABLE bad_drivers (
"state" VARCHAR,
"number_of_drivers_involved_in_fatal_collisions_per_bil_5c925459" DOUBLE,
"percentage_of_drivers_involved_in_fatal_collisions_who_c00d2341" BIGINT,
"percentage_of_drivers_involved_in_fatal_collisions_who_7a6df15b" BIGINT,
"percentage_of_drivers_involved_in_fatal_collisions_who_b16c0b1b" BIGINT,
"percentage_of_drivers_involved_in_fatal_collisions_who_74107392" BIGINT,
"car_insurance_premiums" DOUBLE,
"losses_incurred_by_insurance_companies_for_collisions__74052d1b" DOUBLE
);
CREATE TABLE car_crashes (
"total" DOUBLE,
"speeding" DOUBLE,
"alcohol" DOUBLE,
"not_distracted" DOUBLE,
"no_previous" DOUBLE,
"ins_premium" DOUBLE,
"ins_losses" DOUBLE,
"abbrev" VARCHAR
);
CREATE TABLE flights (
"lon_departure" DOUBLE,
"lat_departure" DOUBLE,
"lon_arrival" DOUBLE,
"lat_arrival" DOUBLE
);
CREATE TABLE liquizpolldata_sheet1_2 (
"quiz_number" BIGINT,
"total_views" BIGINT,
"total_responses" BIGINT,
"right_answers" BIGINT,
"total_likes" BIGINT,
"avg_right" VARCHAR,
"max_right" VARCHAR
);
CREATE TABLE nasdaq_bt_summary (
"stock" VARCHAR,
"total_return" DOUBLE,
"cagr" DOUBLE,
"max_drawdown" DOUBLE,
"calmar" DOUBLE,
"mtd" DOUBLE,
"three_month" DOUBLE,
"six_month" DOUBLE,
"ytd" DOUBLE,
"one_year" DOUBLE,
"three_year" DOUBLE,
"five_year" DOUBLE,
"ten_year" DOUBLE,
"incep" DOUBLE,
"daily_sharpe" DOUBLE,
"daily_sortino" DOUBLE,
"daily_mean" DOUBLE,
"daily_vol" DOUBLE,
"daily_skew" DOUBLE,
"daily_kurt" DOUBLE,
"best_day" DOUBLE,
"worst_day" DOUBLE,
"monthly_sharpe" DOUBLE,
"monthly_sortino" DOUBLE,
"monthly_mean" DOUBLE,
"monthly_vol" DOUBLE,
"monthly_skew" DOUBLE,
"monthly_kurt" DOUBLE,
"best_month" DOUBLE,
"worst_month" DOUBLE,
"yearly_sharpe" DOUBLE,
"yearly_sortino" DOUBLE,
"yearly_mean" DOUBLE,
"yearly_vol" DOUBLE,
"yearly_skew" DOUBLE,
"yearly_kurt" DOUBLE,
"best_year" DOUBLE,
"worst_year" DOUBLE,
"avg_drawdown" DOUBLE,
"avg_drawdown_days" DOUBLE,
"avg_up_month" DOUBLE,
"avg_down_month" DOUBLE,
"win_year_perc" DOUBLE,
"twelve_month_win_perc" DOUBLE
);
CREATE TABLE oecd_health_stat_cancer_statistics (
"var" VARCHAR,
"variable" VARCHAR,
"unit" VARCHAR,
"measure" VARCHAR,
"cou" VARCHAR,
"country" VARCHAR,
"yea" BIGINT,
"year" BIGINT,
"value" DOUBLE,
"flag_codes" VARCHAR,
"flags" VARCHAR
);
CREATE TABLE titanic (
"passengerid" BIGINT,
"survived" BIGINT,
"pclass" BIGINT,
"name" VARCHAR,
"sex" VARCHAR,
"age" DOUBLE,
"sibsp" BIGINT,
"parch" BIGINT,
"ticket" VARCHAR,
"fare" DOUBLE,
"cabin" VARCHAR,
"embarked" VARCHAR
);
CREATE TABLE travel_times (
"date" TIMESTAMP,
"starttime" VARCHAR,
"dayofweek" VARCHAR,
"goingto" VARCHAR,
"distance" DOUBLE,
"maxspeed" DOUBLE,
"avgspeed" DOUBLE,
"avgmovingspeed" DOUBLE,
"fueleconomy" VARCHAR,
"totaltime" DOUBLE,
"movingtime" DOUBLE,
"take407all" VARCHAR,
"comments" VARCHAR
);
CREATE TABLE worldcities (
"city" VARCHAR,
"city_ascii" VARCHAR,
"lat" DOUBLE,
"lng" DOUBLE,
"country" VARCHAR,
"iso2" VARCHAR,
"iso3" VARCHAR,
"admin_name" VARCHAR,
"capital" VARCHAR,
"population" DOUBLE,
"id" BIGINT
);
CREATE TABLE worldpopulation (
"region" VARCHAR,
"subregion" VARCHAR,
"key" VARCHAR,
"value" BIGINT
);
Anyone who has the link will be able to view this.