signal processing – How to extract top frequency of a graph with FFT javascript

I’m using an FFT JS library (github.com/indutny/fft.js/) to extract frequencies from line graph data that get new data points every second.

This is my code:

function getFrequencis(frequencySpectrum, sampleRate, dataLength) {
    const binSize = sampleRate / dataLength;
    var frequenciesDict = {}

    for (let j = 1; j < frequencySpectrum.length; j++) {
      frequenciesDict[j*binSize] = frequencySpectrum[j]
    }

    return frequenciesDict
}


const f = new FFT(32);

const out = f.createComplexArray();


    f.realTransform(out, [1,2,3,4,5,5,4,3,2,1,1,2,3,4,5,5,4,3,2,1,1,2,3,4,5,5,4,3,2,1,2,3]);

getFrequencis(out, 1, 32)

I expect to find that the 0.1 frequency is the strongest, but this is the response I get:

{
    "1": -1,
    "0.03125": 0,
    "0.0625": -1.330508935085469,
    "0.09375": -0.5060331130932036,
    "0.125": -2.7653668647301792,
    "0.15625": -2.082392200292394,
    "0.1875": -17.666465995914333,
    "0.21875": -21.984229521692033,
    "0.25": 3.82842712474619,
    "0.28125": 8.242640687119286,
    "0.3125": 0.947624077129027,
    "0.34375": 4.812059092662567,
    "0.375": -0.15224093497742652,
    "0.40625": 3.613125929752753,
    "0.4375": -0.7634026789260374,
    "0.46875": 2.773999558787147,
    "0.5": -1,
    "0.53125": 2,
    "0.5625": -0.3599059628302478,
    "0.59375": 1.0688810757972436,
    "0.625": -3.8477590650225735,
    "0.65625": 1.6131259297527532,
    "0.6875": -2.2684947746976585,
    "0.71875": 0.6627612703477461,
    "0.75": -1.82842712474619,
    "0.78125": 0.24264068711928477,
    "0.8125": -1.4979446807556052,
    "0.84375": 0.008608279724096946,
    "0.875": -1.2346331352698205,
    "0.90625": -0.0823922002923938,
    "0.9375": -1.0609010489196744,
    "0.96875": -0.06901597235215756,
    "1.03125": 0,
    "1.0625": -0.41421356237309515,
    "1.09375": 0.1715728752538097,
    "1.125": 0,
    "1.15625": 0,
    "1.1875": 2.414213562373096,
    "1.21875": -5.82842712474619,
    "1.25": -4,
    "1.28125": 0,
    "1.3125": -3,
    "1.34375": 0,
    "1.375": 7,
    "1.40625": 0,
    "1.4375": 3,
    "1.46875": 0,
    "1.5": 25,
    "1.53125": 0,
    "1.5625": 0.8786796564403576,
    "1.59375": 0.2928932188134523,
    "1.625": 0,
    "1.65625": 1,
    "1.6875": 5.121320343559643,
    "1.71875": -1.7071067811865475,
    "1.75": -5,
    "1.78125": 0,
    "1.8125": -1,
    "1.84375": 0,
    "1.875": 8,
    "1.90625": 0,
    "1.9375": 2,
    "1.96875": 0
}

Two questions:

1. why 0.09375 frequency is not the strongest amplitude?
2. Why do I get negative amplitudes if the graph is only positive?

Thanks!