This ipython notebook takes output data from a 96-well Plate Fluorescence Spectrophotometer, and reorganizes and summarizes the data so that chemists can more easily analyze for patterns.

The original output data from a Plate Reader is a text file that approximates the layout of the well-plate. This notebook script transforms the data to output two new files.

Users can specify different numbers for well_groupings which map to compounds in the output data, and relabel compounds and row concentrations to more accurately identify the values.

37.00	4.4886	0.74	0.7452	0.7466	0.74	0.746	0.7412	0.744	0.7438	0.7462	0.7474	0.7432		

	3689.802	3409.322	3778.041	3079.057	2818.387	2788.283	2845.285	3284.842	3649.555	3456.887	3660.852	3742.566		

The first value (37.00) is a temperature reading. The subsequent values in the first row are time readings. The second row contains corresponding fluorescence readings for each time. This is repeated for each row in the plate, with a break in between.

(same data as above, formatted to show each well-reading individually)

(further groups data by plate, row, and compound, and provides average stats)

To make it easier to analyze the output data for active compounds, and create charts for research.

Python 2.7 Required packages: csv, pandas, numpy, decimal