7 DuckDB SQL 쿼리는 몇 시간의 팬더 작업을 절약 할 수 있습니다.

import pandas as pd
df = pd.read_csv("dataset_2.csv")

import duckdb
con = duckdb.connect()

con.register("my_data", df)

SELECT 
    *
FROM data
WHERE condition_1
  AND condition_2
  AND condition_3
  AND condition_4

filtered_df = df[
    (df["condition_1"]) &
    (df["condition_2"]) &
    (df["condition_3"]) &
    (df["condition_4"])
]

SELECT 
    COUN(*) AS qualified_drivers,
    COUNT(*) * 50 AS total_payout
FROM data
WHERE "Supply Hours" >= 8
  AND CAST(REPLACE("Accept Rate", '%', '') AS DOUBLE) >= 90
  AND "Trips Completed" >= 10
  AND Rating >= 4.7

con.execute("""
SELECT 
    COUNT(*) AS qualified_drivers,
    COUNT(*) * 50 AS total_payout
FROM data
WHERE "Supply Hours" >= 8
  AND CAST(REPLACE("Accept Rate", '%', '') AS DOUBLE) >= 90
  AND "Trips Completed" >= 10
  AND Rating >= 4.7
""").fetchdf()

SELECT 
    COUNT(*) AS num_rows,
    SUM(column_name) AS total_value
FROM data
WHERE some_condition

filtered = df[df["some_condition"]]
num_rows = filtered.shape[0]
total_value = filtered["column_name"].sum()

SELECT 
    COUNT(*) AS qualified_drivers,
    SUM("Trips Completed") * 4 AS total_payout
FROM data
WHERE "Trips Completed" >= 12
  AND Rating >= 4.7

SELECT *
FROM data
WHERE condition_a
  AND condition_b
  AND NOT (condition_c)

filtered = df[
    (df["condition_a"]) &
    (df["condition_b"]) &
    ~(df["condition_c"])
]

SELECT COUNT(*) AS only_option1
FROM data
WHERE "Supply Hours" >= 8
  AND CAST(REPLACE("Accept Rate", '%', '') AS DOUBLE) >= 90
  AND "Trips Completed" >= 10
  AND Rating >= 4.7
  AND NOT ("Trips Completed" >= 12 AND Rating >= 4.7)

SELECT 
  ROUND(100.0 * COUNT(*) / (SELECT COUNT(*) FROM data), 2) AS percentage
FROM data
WHERE condition_1
  AND condition_2
  AND condition_3

filtered = df[
    (df["condition_1"]) &
    (df["condition_2"]) &
    (df["condition_3"])
]
percentage = round(100.0 * len(filtered) / len(df), 2)

SELECT 
  ROUND(100.0 * COUNT(*) / (SELECT COUNT(*) FROM data), 2) AS percentage
FROM data
WHERE "Trips Completed" 

SELECT 
    daily_income * work_days * weeks_per_year AS annual_revenue,
    weekly_cost * weeks_per_year AS total_cost,
    (daily_income * work_days * weeks_per_year) - (weekly_cost * weeks_per_year) AS net_income
FROM data

daily_income = 200
weeks_per_year = 49
work_days = 6
weekly_cost = 500

annual_revenue = daily_income * work_days * weeks_per_year
total_cost = weekly_cost * weeks_per_year
net_income = annual_revenue - total_cost

SELECT 
    200 * 6 * (52 - 3) AS annual_revenue,
    200 * (52 - 3) AS gas_expense,
    500 * (52 - 3) AS rent_expense,
    400 * 12 AS insurance_expense,
    (200 * 6 * (52 - 3)) 
      - (200 * (52 - 3) + 500 * (52 - 3) + 400 * 12) AS net_income

SELECT 
    original_cost * 1.05 AS increased_cost,
    original_cost * 0.8 AS discounted_cost,
    0 AS removed_cost,
    (original_cost * 1.05 + original_cost * 0.8) AS total_new_cost

weeks_worked = 49
gas = 200
insurance = 400

gas_expense = gas * 1.05 * weeks_worked
insurance_expense = insurance * 0.8 * 12
rent_expense = 0
total = gas_expense + insurance_expense

con.execute("""
SELECT 
    200 * 1.05 * 49 AS gas_expense,
    400 * 0.8 * 12 AS insurance_expense,
    0 AS rent_expense,
    (200 * 1.05 * 49) + (400 * 0.8 * 12) AS total_expense
""").fetchdf()

WITH vars AS (
  SELECT base_income, cost_1, cost_2, target_item
),
calc AS (
  SELECT 
    base_income - (cost_1 + cost_2) AS current_profit,
    cost_1 * 1.1 + cost_2 * 0.8 + target_item AS new_total_expense
  FROM vars
),
final AS (
  SELECT 
    current_profit + new_total_expense AS required_revenue,
    required_revenue / 49 AS required_weekly_income
  FROM calc
)
SELECT required_weekly_income FROM final

weeks = 49
original_income = 200 * 6 * weeks
original_cost = (200 + 500) * weeks + 400 * 12
net_income = original_income - original_cost

# new expenses + car cost
new_gas = 200 * 1.05 * weeks
new_insurance = 400 * 0.8 * 12
car_cost = 40000

required_revenue = net_income + new_gas + new_insurance + car_cost
required_weekly_income = required_revenue / weeks

WITH vars AS (
  SELECT 
    52 AS total_weeks_per_year,
    3 AS weeks_off,
    6 AS days_per_week,
    200 AS fare_per_day,
    400 AS monthly_insurance,
    200 AS gas_per_week,
    500 AS vehicle_rent,
    40000 AS car_cost
),
base AS (
  SELECT 
    total_weeks_per_year,
    weeks_off,
    days_per_week,
    fare_per_day,
    monthly_insurance,
    gas_per_week,
    vehicle_rent,
    car_cost,
    total_weeks_per_year - weeks_off AS weeks_worked,
    (fare_per_day * days_per_week * (total_weeks_per_year - weeks_off)) AS original_annual_revenue,
    (gas_per_week * (total_weeks_per_year - weeks_off)) AS original_gas,
    (vehicle_rent * (total_weeks_per_year - weeks_off)) AS original_rent,
    (monthly_insurance * 12) AS original_insurance
  FROM vars
),
compare AS (
  SELECT *,
    (original_gas + original_rent + original_insurance) AS original_total_expense,
    (original_annual_revenue - (original_gas + original_rent + original_insurance)) AS original_net_income
  FROM base
),
new_costs AS (
  SELECT *,
    gas_per_week * 1.05 * weeks_worked AS new_gas,
    monthly_insurance * 0.8 * 12 AS new_insurance
  FROM compare
),
final AS (
  SELECT *,
    new_gas + new_insurance + car_cost AS new_total_expense,
    original_net_income + new_gas + new_insurance + car_cost AS required_revenue,
    required_revenue / weeks_worked AS required_weekly_revenue,
    original_annual_revenue / weeks_worked AS original_weekly_revenue
  FROM new_costs
)
SELECT 
  ROUND(required_weekly_revenue, 2) AS required_weekly_revenue,
  ROUND(required_weekly_revenue - original_weekly_revenue, 2) AS weekly_uplift
FROM final