My goal is to determine the maximum value for 15-minute data that I am extracting from a .csv file. Each row in the file represents 15-minutes of data from a different source identified by "ID" on a specific day indicated by "Date". However, there are unnecessary columns such as "Class", "Sample", and "Channel" that are not relevant to my analysis.
I initially considered using d3.group, but having five key values corresponding to the non-numeric attributes does not seem to be the most effective approach.
The format of the imported data is as follows:
[
{
"ID": "10D1012B",
"Class": "R",
"Sample": "135_OLD",
"Channel": "1",
"Date": "1/1/2019",
"00:15": "0.48",
"00:30": "0.6",
"00:45": "0.896",
"01:00": "0.712",
"01:15": "1.12",
...
"23:00": "0.48",
"23:15": "0.6",
"23:30": "0.624",
"23:45": "0.552",
"00:00": "0.704"
},
{
"ID": "10D1040B",
"Class": "R",
"Sample": "135_OLD",
"Channel": "1",
"Date": "1/2/2019",
"00:15": "1.016",
...
"23:30": "0.632",
"23:45": "0.72",
"00:00": "0.776"
}
]
To establish the chart scale, I need to compute the highest value within each row of data (identified by ID and Date). However, I am unsure about the appropriate method to exclude the non-numeric columns when determining the maximum value.