Classwork 7

Reshaping DataFrames; Joining DataFrames; Data Visualization

Author

Byeong-Hak Choe

Published

March 19, 2024

Modified

March 24, 2024

Part 1 - Pivoting DataFrames

Question 1

  • Make ny_pincp longer.
ny_pincp = pd.read_csv('https://bcdanl.github.io/data/NY_pinc_wide.csv')

Answer:


Question 2

  • Make a wide-form DataFrame of covid whose variable names are from countriesAndTerritories and values are from cases.
covid = pd.read_csv('https://bcdanl.github.io/data/covid19_cases.csv')

Answer:



Part 2 - Joining DataFrames



  • The CSV files are related each other, as described above.
flights = pd.read_csv("https://bcdanl.github.io/data/flights.zip")
airlines = pd.read_csv("https://bcdanl.github.io/data/airlines.csv")
airports = pd.read_csv("https://bcdanl.github.io/data/airports.csv")
planes = pd.read_csv("https://bcdanl.github.io/data/planes.csv")
weather = pd.read_csv("https://bcdanl.github.io/data/weather.csv")

Variables in flights DataFrame

  • year, month, day

    • Date of departure.

  • dep_time, arr_time

    • Actual departure and arrival times (format HHMM or HMM), local tz.

  • sched_dep_time, sched_arr_time

    • Scheduled departure and arrival times (format HHMM or HMM), local tz.

  • dep_delay, arr_delay

    • Departure and arrival delays, in minutes. Negative times represent early departures/arrivals.

  • carrier

    • Two letter carrier abbreviation. See airlines DataFrame to get full names.

  • flight Flight number.

  • tailnum

    • Plane tail number. See planes DataFrame for additional metadata.

  • origin, dest

    • Origin and destination. See airports DataFrame for additional metadata.

  • air_time

    • Amount of time spent in the air, in minutes.

  • distance

    • Distance between airports, in miles.

  • hour, minute

    • Time of scheduled departure broken into hour and minutes.

  • time_hour

    • Scheduled date and hour of the flight as a datetime64. Along with origin, can be used to join flights data to weather DataFrame


Question 3

Merge flights with weather.

Answer:


Question 4

Identify the full name of the airline with the highest average dep_delay, considering only positive delays.

Answer:



Discussion

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