Modern.ipynb

@andportnoy, replace
df = pd.read_csv(fp, parse_dates="FL_DATE").rename(columns=str.lower)
with
df = pd.read_csv(fp, parse_dates=["FL_DATE"]).rename(columns=str.lower)

@TomAugspurger, thanks for this great resource

I was not able to use cells 1 through 3 to download the data. I downloaded the data manually and it appears that the format has changed a bit. "FL_DATE" is now "FlightDate" for example. Thank you for writing these "not exactly for beginners" tutorials.

Hi @sbraden , You can open this link https://www.transtats.bts.gov/DL_SelectFields.asp?Table_ID=236&DB_Short_Name=On-Time in your browser, choose year to 2014, tick the items in the following list, and then click the 'Download' button on the right. You will get a zip file that should satisfy you.

FL_DATE
UNIQUE_CARRIER
AIRLINE_ID
TAIL_NUM
FL_NUM
ORIGIN_AIRPORT_ID
ORIGIN_AIRPORT_SEQ_ID
ORIGIN_CITY_MARKET_ID
ORIGIN
ORIGIN_CITY_NAME
ORIGIN_STATE_NM
DEST_AIRPORT_ID
DEST_AIRPORT_SEQ_ID
DEST_CITY_MARKET_ID
DEST
DEST_CITY_NAME
DEST_STATE_NM
CRS_DEP_TIME
DEP_TIME
DEP_DELAY
TAXI_OUT
WHEELS_OFF
WHEELS_ON
TAXI_IN
CRS_ARR_TIME
ARR_TIME
ARR_DELAY
CANCELLED
CANCELLATION_CODE
DIVERTED
DISTANCE
CARRIER_DELAY
WEATHER_DELAY
NAS_DELAY
SECURITY_DELAY
LATE_AIRCRAFT_DELAY