Reference no: EM13979093

The sample above shows all three of the types of input that will be found in our tests. All the input will start with a header line like the one at the top of the input and it should be ignored. Let me explain each of the columns in the data

1. STATION - this is the official station identification. We won't be displaying this.
2. STATION_NAME - this is the name for the station. In our summary, we will be displaying this.
3. ELEVATION - this is the elevation for the station. We will be displaying this.
4. LATITUDE - this is the latitude of the station. We will be displaying this.
5. LONGITUDE - this is the longitude of the station. We will be displaying this.
6. DATE - this is the date for the reading. We won't be displaying this.
7. TPCP - this is the total precipitation recorded by the station in tenths of a millimeter. We will be displaying this but it will be converted to inches.
8. Missing - this is a number representing how many days in the month there was missing data. We will not be displaying this data.
9. Consecutive - this is a number of consecutive days when the precipitation was not recorded. We will not be displaying this data.
10. MNTM - this is the mean temperature recorded by the station. -9999 indicates it wasn't recorded. If it was recorded it is in Celsius.  It is recorded in tenths of a degree.  So for example 12 is really 1.2 degrees Celsius. We will be displaying this in Fahrenheit. If a station shows -9999 then we will use 0 for that report.
11. Missing - this is a number representing how many days in the month there was missing data. We will not be displaying this data.
12. Consecutive - this is a number of consecutive days when the temperature was not recorded. We will not be displaying this data.

The set of data for Culpeper is what I'm calling good data. It has most of the data but it is missing temperature data. That is represented by the -9999. It has all 12 months of data and so we would display this data. See the output below.

The set of data for Corbin is what I'm call all good data. It has all of the data recorded for it, including the temperature and it has all 12 months of data. See the output below.

The set of data for Amelia is what I'm calling bad data because it only has 8 months worth of data. Any set of data that is fewer than 12 months is "bad data". See the output below.