--- title: Featurizing Time Series keywords: fastai sidebar: home_sidebar summary: "Functions used to transform time series into a dataframe that can be used to create tabular dataloaders." description: "Functions used to transform time series into a dataframe that can be used to create tabular dataloaders." nb_path: "nbs/020_data.features.ipynb" ---
{% raw %}
{% endraw %} {% raw %}
{% endraw %} {% raw %}
{% endraw %}

In this case we are using tsfresh that is one of the most widely known libraries used to create features from time series. You can get more details about this library here: https://tsfresh.readthedocs.io/en/latest/

{% raw %}

get_ts_features[source]

get_ts_features(X:Union[ndarray, Tensor], y:Union[NoneType, ndarray, Tensor]=None, features:Union[str, dict]='min', n_jobs:Optional[int]=None, **kwargs)

Args: X: np.array or torch.Tesnor of shape [samples, dimensions, timesteps]. y: Not required for unlabeled data. Otherwise, you need to pass it. features: 'min', 'efficient', 'all', or a dictionary. Be aware that 'efficient' and 'all' may required substantial memory and time.

{% endraw %} {% raw %}
{% endraw %} {% raw %}
dsid = 'NATOPS'
X, y, splits = get_UCR_data(dsid, return_split=False)
X.shape
(360, 24, 51)
{% endraw %}

There are 3 levels of fatures you can extract: 'min', 'efficient' and 'all'. I'd encourage you to start with min as feature creation may take a long time.

In addition to this, you can pass a dictionary to build the desired features (see tsfresh documentation in the link above).

{% raw %}
ts_features_df = get_ts_features(X, y)
ts_features_df.shape
Feature Extraction: 100%|█████████████████████████████████| 40/40 [00:06<00:00,  6.22it/s]
(360, 217)
{% endraw %}

The 'min' set creates a dataframe with 8 features per channel + 1 per target (total 193) for each time series sample (360).

{% raw %}
cont_names = ts_features_df.columns[:-1]
y_names = 'target'
dls = get_tabular_dls(ts_features_df, splits=splits, cont_names=cont_names, y_names=y_names)
dls.show_batch()
0__sum_values 0__median 0__mean 0__length 0__standard_deviation 0__variance 0__root_mean_square 0__maximum 0__minimum 1__sum_values 1__median 1__mean 1__length 1__standard_deviation 1__variance 1__root_mean_square 1__maximum 1__minimum 2__sum_values 2__median 2__mean 2__length 2__standard_deviation 2__variance 2__root_mean_square 2__maximum 2__minimum 3__sum_values 3__median 3__mean 3__length 3__standard_deviation 3__variance 3__root_mean_square 3__maximum 3__minimum 4__sum_values 4__median 4__mean 4__length 4__standard_deviation 4__variance 4__root_mean_square 4__maximum 4__minimum 5__sum_values 5__median 5__mean 5__length 5__standard_deviation 5__variance 5__root_mean_square 5__maximum 5__minimum 6__sum_values 6__median 6__mean 6__length 6__standard_deviation 6__variance 6__root_mean_square 6__maximum 6__minimum 7__sum_values 7__median 7__mean 7__length 7__standard_deviation 7__variance 7__root_mean_square 7__maximum 7__minimum 8__sum_values 8__median 8__mean 8__length 8__standard_deviation 8__variance 8__root_mean_square 8__maximum 8__minimum 9__sum_values 9__median 9__mean 9__length 9__standard_deviation 9__variance 9__root_mean_square 9__maximum 9__minimum 10__sum_values 10__median 10__mean 10__length 10__standard_deviation 10__variance 10__root_mean_square 10__maximum 10__minimum 11__sum_values 11__median 11__mean 11__length 11__standard_deviation 11__variance 11__root_mean_square 11__maximum 11__minimum 12__sum_values 12__median 12__mean 12__length 12__standard_deviation 12__variance 12__root_mean_square 12__maximum 12__minimum 13__sum_values 13__median 13__mean 13__length 13__standard_deviation 13__variance 13__root_mean_square 13__maximum 13__minimum 14__sum_values 14__median 14__mean 14__length 14__standard_deviation 14__variance 14__root_mean_square 14__maximum 14__minimum 15__sum_values 15__median 15__mean 15__length 15__standard_deviation 15__variance 15__root_mean_square 15__maximum 15__minimum 16__sum_values 16__median 16__mean 16__length 16__standard_deviation 16__variance 16__root_mean_square 16__maximum 16__minimum 17__sum_values 17__median 17__mean 17__length 17__standard_deviation 17__variance 17__root_mean_square 17__maximum 17__minimum 18__sum_values 18__median 18__mean 18__length 18__standard_deviation 18__variance 18__root_mean_square 18__maximum 18__minimum 19__sum_values 19__median 19__mean 19__length 19__standard_deviation 19__variance 19__root_mean_square 19__maximum 19__minimum 20__sum_values 20__median 20__mean 20__length 20__standard_deviation 20__variance 20__root_mean_square 20__maximum 20__minimum 21__sum_values 21__median 21__mean 21__length 21__standard_deviation 21__variance 21__root_mean_square 21__maximum 21__minimum 22__sum_values 22__median 22__mean 22__length 22__standard_deviation 22__variance 22__root_mean_square 22__maximum 22__minimum 23__sum_values 23__median 23__mean 23__length 23__standard_deviation 23__variance 23__root_mean_square 23__maximum 23__minimum target
0 -26.125748 -0.617197 -0.512270 51.0 0.943701 0.890571 1.073774 1.078415 -1.911673 -34.008759 0.149119 -0.666838 51.0 1.255401 1.576032 1.421515 0.835408 -2.468259 -54.771980 -1.170985 -1.073960 51.0 0.654869 0.428854 1.257873 0.191203 -2.414801 45.089352 0.785930 0.884105 51.0 0.809274 0.654924 1.198568 2.188559 -0.348977 -43.958305 -0.416730 -0.861928 51.0 1.243240 1.545645 1.512800 0.828457 -2.767821 -6.500301 -0.273865 -0.127457 51.0 0.692578 0.479664 0.704208 1.395830 -1.101830 -32.830414 -0.733551 -0.643734 51.0 0.371831 0.138258 0.743405 0.026682 -1.213494 -13.595337 0.037761 -0.266575 51.0 0.551894 0.304587 0.612903 0.337016 -1.050993 -38.439110 -0.703090 -0.753708 51.0 0.165370 0.027347 0.771637 -0.536640 -1.041002 43.024174 0.858496 0.843611 51.0 0.234376 0.054932 0.875564 1.316007 0.467817 -33.416515 -0.767974 -0.655226 51.0 0.372972 0.139108 0.753942 0.107275 -1.236332 14.994287 0.265541 0.294006 51.0 0.329174 0.108356 0.441356 0.714693 -0.565684 -28.675285 -0.679008 -0.562261 51.0 0.830140 0.689133 1.002631 0.846332 -1.854386 -25.814552 0.195735 -0.506168 51.0 1.006707 1.013460 1.126794 0.666785 -1.962527 -52.758053 -1.041937 -1.034472 51.0 0.400397 0.160318 1.109256 -0.326849 -2.073975 44.222355 0.784457 0.867105 51.0 0.484358 0.234603 0.993214 1.639258 0.045550 -39.218185 -0.404588 -0.768984 51.0 0.888327 0.789125 1.174930 0.425818 -2.121938 1.787856 -0.011863 0.035056 51.0 0.532121 0.283153 0.533274 1.010188 -0.878925 -27.474291 -0.532559 -0.538712 51.0 0.895698 0.802274 1.045220 0.991809 -1.877237 -33.264549 -0.046373 -0.652246 51.0 1.127769 1.271863 1.302800 0.679967 -2.372548 -54.200115 -1.101856 -1.062747 51.0 0.553234 0.306068 1.198123 -0.108695 -2.430505 43.973232 0.814364 0.862220 51.0 0.685167 0.469453 1.101307 2.070084 -0.269295 -40.097370 -0.271559 -0.786223 51.0 1.061406 1.126582 1.320882 0.650062 -2.395347 -3.599012 -0.272136 -0.070569 51.0 0.552809 0.305598 0.557295 1.181493 -0.793739 5.0
1 -23.032122 -0.453522 -0.451610 51.0 0.020624 0.000425 0.452081 -0.407367 -0.483523 -95.011665 -1.890790 -1.862974 51.0 0.079996 0.006399 1.864691 -1.737508 -1.994908 -40.293446 -0.797339 -0.790068 51.0 0.021364 0.000456 0.790356 -0.753447 -0.832328 69.530144 1.556758 1.363336 51.0 0.689258 0.475076 1.527665 2.254283 0.538239 -53.183857 -1.576232 -1.042821 51.0 0.976627 0.953801 1.428732 0.333219 -2.076703 -19.683250 -0.378620 -0.385946 51.0 0.321886 0.103611 0.502558 0.116133 -0.749210 -28.955948 -0.574249 -0.567764 51.0 0.018119 0.000328 0.568053 -0.535390 -0.590395 -37.870449 -0.739721 -0.742558 51.0 0.012710 0.000162 0.742667 -0.718889 -0.773737 -8.419323 -0.173264 -0.165085 51.0 0.028264 0.000799 0.167487 -0.122926 -0.219416 41.896557 0.901153 0.821501 51.0 0.265423 0.070449 0.863315 1.146472 0.486449 -18.767262 -0.609035 -0.367986 51.0 0.451615 0.203956 0.582554 0.264025 -0.815706 -4.138548 0.001693 -0.081148 51.0 0.169715 0.028803 0.188118 0.167638 -0.303604 -26.457359 -0.519180 -0.518772 51.0 0.012153 0.000148 0.518914 -0.476776 -0.544607 -72.847206 -1.427344 -1.428377 51.0 0.052339 0.002739 1.429335 -1.327009 -1.540307 -27.314379 -0.537814 -0.535576 51.0 0.028219 0.000796 0.536319 -0.488411 -0.584014 60.185146 1.336457 1.180101 51.0 0.499599 0.249599 1.281498 1.788841 0.587294 -37.445534 -1.106872 -0.734226 51.0 0.792501 0.628058 1.080346 0.365772 -1.613524 -14.103150 -0.228461 -0.276532 51.0 0.263366 0.069362 0.381879 0.085201 -0.595251 -17.882154 -0.352879 -0.350630 51.0 0.017061 0.000291 0.351045 -0.302203 -0.371365 -81.185501 -1.586450 -1.591872 51.0 0.069167 0.004784 1.593374 -1.474687 -1.714867 -39.537815 -0.774836 -0.775251 51.0 0.038162 0.001456 0.776190 -0.712498 -0.844467 65.537247 1.495586 1.285044 51.0 0.662017 0.438266 1.445546 2.076030 0.409335 -48.222878 -1.484378 -0.945547 51.0 0.833462 0.694659 1.260443 0.219000 -1.857067 -19.146971 -0.337882 -0.375431 51.0 0.299121 0.089474 0.480023 0.008158 -0.814267 3.0
2 -55.967842 -1.393075 -1.097409 51.0 1.041536 1.084798 1.512978 0.554320 -2.226613 -7.324898 0.038845 -0.143625 51.0 0.921892 0.849885 0.933013 1.178867 -1.823300 -10.047729 -0.202519 -0.197014 51.0 0.446699 0.199540 0.488216 0.534370 -1.079120 41.135918 0.903621 0.806587 51.0 0.807219 0.651602 1.141133 1.760939 -0.359942 -8.660412 0.029534 -0.169812 51.0 0.929820 0.864564 0.945199 1.129257 -1.847907 -28.565268 -0.545492 -0.560103 51.0 0.179385 0.032179 0.588128 -0.266289 -0.959156 -44.885334 -0.967861 -0.880105 51.0 0.238675 0.056966 0.911893 -0.469294 -1.170743 -9.256048 -0.172775 -0.181491 51.0 0.307751 0.094710 0.357281 0.406037 -0.687671 0.463085 0.107722 0.009080 51.0 0.280720 0.078804 0.280867 0.338852 -0.679018 41.644283 0.802014 0.816555 51.0 0.234215 0.054857 0.849481 1.132215 0.450928 -16.054821 -0.257364 -0.314800 51.0 0.387505 0.150160 0.499259 0.164928 -1.025835 -21.814440 -0.333916 -0.427734 51.0 0.189298 0.035834 0.467750 -0.244958 -0.901380 -52.815643 -1.219906 -1.035601 51.0 0.683794 0.467574 1.240985 0.066124 -1.800773 -10.226376 -0.210734 -0.200517 51.0 0.651131 0.423971 0.681306 0.786237 -1.358352 -5.322519 -0.156819 -0.104363 51.0 0.372799 0.138979 0.387132 0.491980 -0.892873 43.758427 0.908243 0.858008 51.0 0.594778 0.353761 1.044002 1.605851 0.005005 -11.192875 -0.075961 -0.219468 51.0 0.678406 0.460234 0.713022 0.720854 -1.407796 -27.702219 -0.529891 -0.543181 51.0 0.142636 0.020345 0.561596 -0.263660 -0.862570 -56.562233 -1.263201 -1.109063 51.0 0.852080 0.726041 1.398593 0.267139 -2.110844 -6.812057 0.103374 -0.133570 51.0 0.810661 0.657171 0.821591 1.075167 -1.612970 -11.455296 -0.204729 -0.224614 51.0 0.410750 0.168716 0.468153 0.476780 -1.126326 40.317799 0.851637 0.790545 51.0 0.701223 0.491713 1.056728 1.672093 -0.308167 -11.604115 -0.074963 -0.227532 51.0 0.785664 0.617268 0.817948 0.921186 -1.566342 -28.539072 -0.579538 -0.559590 51.0 0.212565 0.045184 0.598602 -0.164424 -1.016220 4.0
3 -4.150354 -0.432566 -0.081380 51.0 0.597360 0.356840 0.602878 0.778331 -0.861279 -58.627594 -1.552286 -1.149561 51.0 0.601466 0.361761 1.297401 -0.056605 -1.699415 -45.035744 -0.893296 -0.883054 51.0 0.181012 0.032765 0.901415 -0.495560 -1.175184 38.219048 0.796074 0.749393 51.0 0.234144 0.054824 0.785120 1.111021 0.392384 -38.509396 -1.455609 -0.755086 51.0 1.031962 1.064946 1.278711 0.693374 -1.788006 -31.586580 -0.608169 -0.619345 51.0 0.421872 0.177976 0.749376 0.048263 -1.458466 -31.067938 -0.635204 -0.609175 51.0 0.081749 0.006683 0.614636 -0.482192 -0.746402 -31.909603 -0.629038 -0.625678 51.0 0.036791 0.001354 0.626759 -0.535260 -0.697649 -17.736265 -0.304125 -0.347770 51.0 0.087451 0.007648 0.358597 -0.237202 -0.495997 32.072475 0.629244 0.628872 51.0 0.025069 0.000628 0.629372 0.705176 0.578095 -29.936869 -0.710722 -0.586997 51.0 0.179691 0.032289 0.613885 -0.265087 -0.757163 -12.696542 -0.096251 -0.248952 51.0 0.292832 0.085750 0.384353 0.064884 -0.710493 -15.762158 -0.560294 -0.309062 51.0 0.451446 0.203804 0.547104 0.387947 -0.861255 -50.898941 -1.250778 -0.998018 51.0 0.350596 0.122918 1.057808 -0.417412 -1.338018 -37.527363 -0.719907 -0.735831 51.0 0.064895 0.004211 0.738687 -0.624461 -0.893202 36.929703 0.767098 0.724112 51.0 0.122116 0.014912 0.734336 0.937925 0.508076 -35.144825 -1.175173 -0.689114 51.0 0.687803 0.473073 0.973628 0.371802 -1.436428 -22.387865 -0.307232 -0.438978 51.0 0.260977 0.068109 0.510696 -0.122424 -1.079398 -12.441168 -0.456977 -0.243944 51.0 0.540300 0.291924 0.592817 0.543158 -0.968512 -55.026745 -1.469483 -1.078956 51.0 0.552103 0.304817 1.212008 -0.084885 -1.574698 -38.722870 -0.801516 -0.759272 51.0 0.202432 0.040979 0.785794 -0.339747 -1.160803 36.171883 0.779261 0.709253 51.0 0.187150 0.035025 0.733529 1.006178 0.436847 -39.467243 -1.469226 -0.773867 51.0 0.965357 0.931915 1.237249 0.637314 -1.777838 -30.077049 -0.508991 -0.589746 51.0 0.351033 0.123224 0.686312 -0.159678 -1.447092 6.0
4 -24.240414 -0.466537 -0.475302 51.0 0.029018 0.000842 0.476187 -0.429550 -0.529862 -100.325508 -2.023705 -1.967167 51.0 0.128641 0.016549 1.971369 -1.742917 -2.109735 -47.944283 -0.955713 -0.940084 51.0 0.052114 0.002716 0.941527 -0.847479 -1.012114 62.371391 0.944372 1.222968 51.0 0.575900 0.331660 1.351781 1.966548 0.606128 -76.945488 -2.157267 -1.508735 51.0 0.892595 0.796726 1.752999 0.041167 -2.268757 18.927240 0.160878 0.371122 51.0 0.503925 0.253940 0.625837 1.094639 -0.181322 -34.801472 -0.702194 -0.682382 51.0 0.039176 0.001535 0.683505 -0.610830 -0.736732 -40.525074 -0.821436 -0.794609 51.0 0.041125 0.001691 0.795673 -0.729676 -0.841635 -19.432070 -0.387849 -0.381021 51.0 0.024914 0.000621 0.381835 -0.340104 -0.418090 36.741726 0.646333 0.720426 51.0 0.177184 0.031394 0.741895 0.992896 0.547114 -36.703846 -0.836233 -0.719683 51.0 0.276144 0.076255 0.770843 -0.194008 -1.037515 16.514927 0.303213 0.323822 51.0 0.203963 0.041601 0.382703 0.585288 0.038468 -30.165279 -0.600986 -0.591476 51.0 0.033534 0.001125 0.592426 -0.531248 -0.640907 -76.733276 -1.567197 -1.504574 51.0 0.109579 0.012008 1.508559 -1.313735 -1.619704 -39.242615 -0.771785 -0.769463 51.0 0.047903 0.002295 0.770953 -0.688118 -0.851190 51.977379 0.835897 1.019164 51.0 0.387951 0.150506 1.090505 1.522439 0.627171 -63.755936 -1.677192 -1.250116 51.0 0.666380 0.444062 1.416634 -0.106297 -1.867931 18.045666 0.288986 0.353837 51.0 0.351358 0.123452 0.498651 0.829620 -0.096027 -22.729506 -0.450052 -0.445677 51.0 0.036626 0.001341 0.447179 -0.362307 -0.496208 -87.243217 -1.762908 -1.710651 51.0 0.107825 0.011626 1.714046 -1.514089 -1.830323 -47.553715 -0.955547 -0.932426 51.0 0.073088 0.005342 0.935286 -0.760686 -1.031647 58.028797 0.819354 1.137820 51.0 0.469457 0.220390 1.230863 1.835938 0.645904 -75.135002 -1.964399 -1.473235 51.0 0.784536 0.615497 1.669108 -0.121420 -2.139044 18.487558 0.348393 0.362501 51.0 0.451555 0.203902 0.579059 1.004090 -0.165228 2.0
5 -27.165516 -0.536883 -0.532657 51.0 0.016744 0.000280 0.532920 -0.502702 -0.560932 -95.997231 -1.898563 -1.882299 51.0 0.053350 0.002846 1.883054 -1.781519 -1.941347 -36.941563 -0.729366 -0.724344 51.0 0.016002 0.000256 0.724521 -0.690236 -0.747808 60.065617 0.948071 1.177757 51.0 0.704257 0.495978 1.372257 2.142466 0.450336 -61.754845 -1.666102 -1.210879 51.0 0.846779 0.717035 1.477587 0.305404 -1.959419 -27.772963 -0.621033 -0.544568 51.0 0.197079 0.038840 0.579132 -0.227260 -0.773908 -34.974701 -0.690630 -0.685778 51.0 0.011427 0.000131 0.685874 -0.662439 -0.699299 -37.919842 -0.746654 -0.743526 51.0 0.018186 0.000331 0.743749 -0.710500 -0.764230 -12.267669 -0.235011 -0.240543 51.0 0.012727 0.000162 0.240879 -0.224520 -0.263516 42.680553 0.693027 0.836874 51.0 0.209641 0.043949 0.862732 1.156850 0.645157 -31.756411 -0.779104 -0.622675 51.0 0.239749 0.057480 0.667236 -0.172677 -0.808979 -3.159732 -0.056477 -0.061956 51.0 0.066736 0.004454 0.091061 0.025393 -0.143102 -32.130642 -0.638684 -0.630013 51.0 0.019284 0.000372 0.630308 -0.595196 -0.652398 -76.102081 -1.503736 -1.492198 51.0 0.041456 0.001719 1.492773 -1.413475 -1.536296 -30.032400 -0.590515 -0.588871 51.0 0.009848 0.000097 0.588953 -0.569854 -0.604554 54.681812 0.907865 1.072192 51.0 0.470966 0.221809 1.171070 1.705159 0.603231 -50.135708 -1.323456 -0.983053 51.0 0.594968 0.353987 1.149078 0.103693 -1.503520 -17.625498 -0.350934 -0.345598 51.0 0.162195 0.026307 0.381766 -0.119397 -0.535905 -36.888882 -0.735077 -0.723311 51.0 0.023801 0.000567 0.723703 -0.678959 -0.750790 -85.593956 -1.694503 -1.678313 51.0 0.051886 0.002692 1.679115 -1.569607 -1.769257 -31.871613 -0.623800 -0.624934 51.0 0.015528 0.000241 0.625126 -0.599763 -0.675700 55.528934 0.865510 1.088803 51.0 0.702024 0.492837 1.295503 2.047369 0.374317 -57.945110 -1.562730 -1.136179 51.0 0.676655 0.457862 1.322408 0.138011 -1.726961 -25.584143 -0.562665 -0.501650 51.0 0.208082 0.043298 0.543094 -0.116376 -0.728259 2.0
6 -14.545370 -0.564797 -0.285203 51.0 0.586768 0.344297 0.652409 0.766090 -1.262017 -68.773376 -1.709308 -1.348498 51.0 0.670194 0.449159 1.505857 -0.036212 -1.911375 -39.266464 -0.744333 -0.769931 51.0 0.247348 0.061181 0.808687 -0.405026 -1.221697 29.541039 0.563878 0.579236 51.0 0.096032 0.009222 0.587143 0.787076 0.429283 -32.622440 -1.265420 -0.639656 51.0 1.285709 1.653047 1.436038 1.107433 -1.980435 -34.056927 -0.537911 -0.667783 51.0 0.337665 0.114017 0.748299 -0.288466 -1.434120 -30.160013 -0.604871 -0.591373 51.0 0.118569 0.014058 0.603142 -0.366325 -0.847400 -33.221859 -0.653152 -0.651409 51.0 0.071559 0.005121 0.655328 -0.537385 -0.765475 -10.395036 -0.130416 -0.203824 51.0 0.152252 0.023181 0.254411 0.011362 -0.467706 32.568321 0.622949 0.638595 51.0 0.033795 0.001142 0.639488 0.726646 0.607346 -23.882542 -0.696731 -0.468285 51.0 0.381310 0.145397 0.603894 0.203091 -0.823671 -17.569372 -0.180988 -0.344498 51.0 0.295452 0.087292 0.453840 -0.040204 -0.746357 -22.151129 -0.609850 -0.434336 51.0 0.414832 0.172085 0.600611 0.397854 -1.129822 -55.078049 -1.276379 -1.079962 51.0 0.410733 0.168702 1.155430 -0.285913 -1.446920 -29.383623 -0.522408 -0.576149 51.0 0.203974 0.041606 0.611190 -0.239105 -0.922754 31.342361 0.601624 0.614556 51.0 0.069625 0.004848 0.618488 0.755640 0.520510 -27.893246 -1.104266 -0.546926 51.0 0.980350 0.961087 1.122593 0.864863 -1.512487 -29.277952 -0.536755 -0.574077 51.0 0.255731 0.065398 0.628461 -0.261470 -1.172555 -20.482330 -0.643489 -0.401614 51.0 0.525879 0.276548 0.661697 0.567971 -1.291647 -62.356918 -1.514664 -1.222685 51.0 0.582776 0.339627 1.354469 -0.035585 -1.770134 -35.743496 -0.690500 -0.700853 51.0 0.249727 0.062363 0.744015 -0.318119 -1.197305 28.363110 0.578135 0.556139 51.0 0.130286 0.016974 0.571196 0.851674 0.378598 -31.734194 -1.322796 -0.622239 51.0 1.149230 1.320730 1.306871 0.970594 -1.831573 -32.540260 -0.481847 -0.638044 51.0 0.326218 0.106418 0.716602 -0.253749 -1.423260 6.0
7 -22.089481 -0.426620 -0.433127 51.0 0.051887 0.002692 0.436224 -0.353775 -0.493256 -79.072937 -1.560552 -1.550450 51.0 0.035141 0.001235 1.550848 -1.475678 -1.623195 -48.691841 -0.953417 -0.954742 51.0 0.021985 0.000483 0.954995 -0.907814 -0.998319 47.297810 0.649993 0.927408 51.0 0.424749 0.180412 1.020048 1.830051 0.447356 -19.371216 -1.533620 -0.379828 51.0 1.421009 2.019268 1.470897 1.603023 -1.656069 -14.617298 -0.637720 -0.286614 51.0 0.478551 0.229011 0.557816 0.564454 -0.663262 -36.714886 -0.733394 -0.719900 51.0 0.051507 0.002653 0.721740 -0.645469 -0.778831 -25.552364 -0.470940 -0.501027 51.0 0.054890 0.003013 0.504025 -0.450767 -0.609533 -6.847224 -0.122346 -0.134259 51.0 0.041205 0.001698 0.140440 -0.079976 -0.189690 37.426327 0.639158 0.733850 51.0 0.173450 0.030085 0.754069 1.164017 0.588437 -13.343306 -0.673153 -0.261633 51.0 0.566572 0.321004 0.624064 0.630515 -0.746939 6.375568 0.068729 0.125011 51.0 0.151819 0.023049 0.196664 0.368656 -0.025980 -28.704739 -0.568022 -0.562838 51.0 0.050026 0.002503 0.565057 -0.490766 -0.616910 -54.063286 -1.046715 -1.060064 51.0 0.033979 0.001155 1.060609 -1.027859 -1.161271 -32.238930 -0.625409 -0.632136 51.0 0.034916 0.001219 0.633099 -0.577443 -0.684264 45.496464 0.672017 0.892088 51.0 0.311601 0.097095 0.944942 1.600711 0.630026 -16.706364 -1.150480 -0.327576 51.0 1.040363 1.082355 1.090716 1.165667 -1.251064 -5.941157 -0.304926 -0.116493 51.0 0.311124 0.096798 0.332218 0.396875 -0.387906 -29.257990 -0.564004 -0.573686 51.0 0.071533 0.005117 0.578129 -0.337868 -0.652336 -76.428627 -1.494161 -1.498600 51.0 0.042848 0.001836 1.499213 -1.412966 -1.614412 -44.839191 -0.880543 -0.879200 51.0 0.030976 0.000959 0.879745 -0.823003 -0.934714 41.487835 0.517329 0.813487 51.0 0.446360 0.199238 0.927900 1.735987 0.444740 -18.961103 -1.415916 -0.371786 51.0 1.268295 1.608572 1.321665 1.450674 -1.501040 -14.482611 -0.537522 -0.283973 51.0 0.351348 0.123445 0.451759 0.273131 -0.644848 1.0
8 -34.139423 -0.634515 -0.669400 51.0 1.062618 1.129156 1.255888 0.909726 -2.385546 -34.700218 -0.129333 -0.680396 51.0 0.901642 0.812959 1.129557 0.540510 -1.939682 -45.672329 -0.805497 -0.895536 51.0 0.263596 0.069483 0.933524 -0.629552 -1.701076 43.724239 0.587055 0.857338 51.0 0.912132 0.831984 1.251804 2.450136 -0.438976 -39.961739 -0.467972 -0.783563 51.0 0.952951 0.908115 1.233729 0.687577 -1.995132 -26.641882 -0.618587 -0.522390 51.0 0.671009 0.450253 0.850379 0.971951 -1.744541 -37.743725 -0.744362 -0.740073 51.0 0.367000 0.134689 0.826073 -0.140920 -1.241213 -17.826847 -0.158973 -0.349546 51.0 0.332063 0.110266 0.482129 0.214802 -0.799246 -20.066814 -0.291549 -0.393467 51.0 0.231769 0.053717 0.456654 -0.135145 -0.872630 39.137386 0.627669 0.767400 51.0 0.262091 0.068692 0.810922 1.254543 0.388054 -22.984592 -0.384928 -0.450678 51.0 0.357023 0.127465 0.574958 0.242472 -0.930208 -8.975382 -0.070153 -0.175988 51.0 0.389768 0.151919 0.427657 0.422765 -0.823468 -35.535824 -0.719982 -0.696781 51.0 0.830650 0.689979 1.084197 0.611062 -1.975756 -27.787731 -0.083431 -0.544857 51.0 0.689276 0.475101 0.878619 0.454474 -1.510881 -37.438770 -0.695787 -0.734094 51.0 0.212400 0.045114 0.764204 -0.485388 -1.330381 41.442875 0.629153 0.812605 51.0 0.649929 0.422408 1.040546 1.972391 -0.249225 -33.647530 -0.391422 -0.659755 51.0 0.690502 0.476794 0.955024 0.550331 -1.587678 -21.662807 -0.444577 -0.424761 51.0 0.530554 0.281488 0.679639 0.684882 -1.261415 -33.445850 -0.541650 -0.655801 51.0 0.959048 0.919773 1.161829 0.673610 -2.328755 -30.276941 -0.214852 -0.593665 51.0 0.770915 0.594310 0.973010 0.415278 -1.668948 -43.124256 -0.714406 -0.845574 51.0 0.274778 0.075503 0.889099 -0.389202 -1.616558 41.945538 0.658312 0.822461 51.0 0.778633 0.606269 1.132569 2.200049 -0.406856 -33.615883 -0.339240 -0.659135 51.0 0.852609 0.726942 1.077683 0.600413 -1.763126 -27.398874 -0.635590 -0.537233 51.0 0.594252 0.353135 0.801096 0.792706 -1.515341 4.0
9 -35.085182 -0.687561 -0.687945 51.0 0.030869 0.000953 0.688637 -0.624283 -0.739868 -106.435272 -2.126637 -2.086966 51.0 0.089233 0.007963 2.088873 -1.959578 -2.215342 -43.562584 -0.854689 -0.854168 51.0 0.032274 0.001042 0.854778 -0.801072 -0.912399 73.886467 1.213113 1.448754 51.0 0.694268 0.482008 1.606517 2.342902 0.642018 -67.402786 -2.043274 -1.321623 51.0 1.021520 1.043502 1.670386 0.217647 -2.288412 -40.294270 -0.799205 -0.790084 51.0 0.048503 0.002353 0.791571 -0.688059 -0.888159 -34.629044 -0.681434 -0.679001 51.0 0.017385 0.000302 0.679223 -0.649223 -0.703762 -40.258858 -0.804071 -0.789389 51.0 0.033163 0.001100 0.790086 -0.741303 -0.842110 -12.998519 -0.267240 -0.254873 51.0 0.017719 0.000314 0.255488 -0.224532 -0.273925 47.912884 0.805694 0.939468 51.0 0.229189 0.052528 0.967020 1.233679 0.697387 -28.587210 -0.880814 -0.560534 51.0 0.403328 0.162674 0.690559 0.038331 -0.921428 -10.081242 -0.202227 -0.197671 51.0 0.030237 0.000914 0.199971 -0.156339 -0.284775 -33.949532 -0.670309 -0.665677 51.0 0.022919 0.000525 0.666072 -0.629390 -0.697200 -85.588051 -1.724138 -1.678197 51.0 0.080795 0.006528 1.680141 -1.563966 -1.791635 -36.548447 -0.725060 -0.716636 51.0 0.030728 0.000944 0.717295 -0.671330 -0.760870 65.181526 1.113361 1.278069 51.0 0.494449 0.244479 1.370380 1.934985 0.748902 -54.790508 -1.635758 -1.074324 51.0 0.817957 0.669053 1.350268 0.139169 -1.839433 -28.428947 -0.573270 -0.557430 51.0 0.053855 0.002900 0.560026 -0.439413 -0.630352 -26.714603 -0.519391 -0.523816 51.0 0.032224 0.001038 0.524806 -0.489540 -0.659033 -93.493767 -1.865099 -1.833211 51.0 0.092432 0.008544 1.835540 -1.700841 -2.010093 -43.577209 -0.860299 -0.854455 51.0 0.049561 0.002456 0.855891 -0.796042 -1.014816 65.893486 1.051441 1.292029 51.0 0.685999 0.470595 1.462851 2.178514 0.574974 -64.151787 -1.856631 -1.257878 51.0 0.804017 0.646444 1.492884 -0.037161 -2.008020 -39.252415 -0.786807 -0.769655 51.0 0.054600 0.002981 0.771589 -0.582144 -0.898071 3.0
{% endraw %} {% raw %}
x_cat, x_cont, yb = first(dls.train)
x_cont[:10]
tensor([[-0.3744,  0.5992, -0.3744,  ...,  1.4033,  2.1748, -0.4065],
        [-0.3864, -0.1467, -0.3864,  ...,  0.8158,  0.3099, -1.5182],
        [-0.0497,  0.0742, -0.0497,  ..., -0.4977, -0.3961,  0.4800],
        ...,
        [ 0.2529,  0.5441,  0.2529,  ..., -0.5928, -0.7302,  0.6398],
        [ 0.8455,  0.3421,  0.8455,  ..., -0.3040, -0.0638, -0.1428],
        [ 0.5438,  0.8348,  0.5438,  ..., -0.4219,  1.5014,  1.7773]])
{% endraw %}