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#    Consensus formation and change are enhanced by neutrality   #
#       A. Sontag, J. Hoffmann, T. Rogers, and C.A. Yates        #
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This folder contains csv files which comprise the data collected from experiments without the option to abstain (for comparison).

####### DATA ORGANISATION AND FORMATTING #########
The data from each experiment is available as .csv files with the naming convention "[group size]_[experiment number with that group size].csv" (e.g., 13_1_noabs.csv is the first experiment with 13 participants).

In each .csv file, the data of each participant corresponds to a line of the table. X votes and Y votes are also denoted A and B, respectively, or numerically as 0 and 1. Abstentions are denoted numerically as 2. The data contains the details of the number of wins of each participant, their rank, if they dropped out, the order of the decision options they were shown in the screen (e.g., [2 1 0] means that the participant saw the Abstention option on the left, voting B in the middle and voting A on the right in the first round), the colours of the voting options and the abstention option and the ID within the group (an index from 1 to the size of the group). This information does not allow for identification of any participants.

The data for each round is presented in subsequent columns of the file. The headers follow the pattern "[type of round (training or experiment)].[round number].[player or group].[property]".

The properties for "player" are participant dependent. They can be the participant's vote in the round ("0" indicates voting A, "1" indicates voting B and "2" indicates abstaining), how much they spent in the round, how much they earned in the round, the sample shown in the round. Properties of the "group" are the same for all participants in the group and are the total number of A, B and Abstain votes in the round, and the winning party (A, B or None - if there was a tie).

################### CODE FILES ####################
The code script comes with inline comments to provide context and explain what task the code is performing. Here is a brief description of each script.

no_abs_plots.py plots the time series data for each experiment, which are plotted in Figure S32 of the Supplementary Information.