diff --git a/actions/stimulus-response/data/20_stimulus-spike-response.html b/actions/stimulus-response/data/20_stimulus-spike-response.html new file mode 100644 index 000000000..b3e298877 --- /dev/null +++ b/actions/stimulus-response/data/20_stimulus-spike-response.html @@ -0,0 +1,15286 @@ + + +
+ +%load_ext autoreload
+%autoreload 2
+
import os
+import expipe
+import pathlib
+import numpy as np
+import spatial_maps.stats as stats
+import septum_mec
+import septum_mec.analysis.data_processing as dp
+import septum_mec.analysis.registration
+import head_direction.head as head
+import spatial_maps as sp
+import speed_cells.speed as spd
+import re
+import joblib
+import multiprocessing
+import shutil
+import psutil
+import pandas as pd
+import matplotlib.pyplot as plt
+import matplotlib
+import seaborn as sns
+from distutils.dir_util import copy_tree
+from neo import SpikeTrain
+import scipy
+
+from tqdm import tqdm_notebook as tqdm
+from tqdm._tqdm_notebook import tqdm_notebook
+tqdm_notebook.pandas()
+
+from spike_statistics.core import permutation_resampling
+
+from spikewaveform.core import calculate_waveform_features_from_template, cluster_waveform_features
+
+from septum_mec.analysis.plotting import violinplot
+
%matplotlib inline
+plt.rc('axes', titlesize=12)
+plt.rcParams.update({
+ 'font.size': 12,
+ 'figure.figsize': (6, 4),
+ 'figure.dpi': 150
+})
+
+output_path = pathlib.Path("output") / "stimulus-response"
+(output_path / "statistics").mkdir(exist_ok=True, parents=True)
+(output_path / "figures").mkdir(exist_ok=True, parents=True)
+output_path.mkdir(exist_ok=True)
+
data_loader = dp.Data()
+actions = data_loader.actions
+project = data_loader.project
+
identification_action = actions['identify-neurons']
+sessions = pd.read_csv(identification_action.data_path('sessions'))
+units = pd.read_csv(identification_action.data_path('units'))
+session_units = pd.merge(sessions, units, on='action')
+
stim_action = actions['stimulus-response']
+stim_results = pd.read_csv(stim_action.data_path('results'))
+
# lfp_results has old unit id's but correct on (action, unit_name, channel_group)
+stim_results = stim_results.drop('unit_id', axis=1)
+
statistics_action = actions['calculate-statistics']
+shuffling = actions['shuffling']
+
+statistics_results = pd.read_csv(statistics_action.data_path('results'))
+statistics_results = session_units.merge(statistics_results, how='left')
+quantiles_95 = pd.read_csv(shuffling.data_path('quantiles_95'))
+action_columns = ['action', 'channel_group', 'unit_name']
+data = pd.merge(statistics_results, quantiles_95, on=action_columns, suffixes=("", "_threshold"))
+
data['unit_day'] = data.apply(lambda x: str(x.unit_idnum) + '_' + x.action.split('-')[1], axis=1)
+
data = data.merge(stim_results, how='left')
+
waveform_action = actions['waveform-analysis']
+waveform_results = pd.read_csv(waveform_action.data_path('results')).drop('template', axis=1)
+
data = data.merge(waveform_results, how='left')
+
colors = ['#d95f02','#e7298a']
+labels = ['11 Hz', '30 HZ']
+queries = ['frequency==11', 'frequency==30']
+
data.bs = data.bs.astype(bool)
+
grid_query = 'gridness > gridness_threshold and information_rate > information_rate_threshold'
+gridcell_sessions = data.query(grid_query)
+print("Number of gridcells", len(gridcell_sessions))
+# print("Number of animals", len(gridcell_sessions.groupby(['entity'])))
+
data['gridcell'] = data.isin(data.query(grid_query))
+
data.query('baseline and gridcell')
+
density = True
+cumulative = True
+histtype = 'step'
+lw = 2
+bins = {
+ 't_i_peak': None,
+ 't_e_peak': None,
+ 'p_i_peak': None,
+ 'p_e_peak': None,
+}
+xlabel = {
+ 't_i_peak': 's',
+ 't_e_peak': 's',
+ 'p_i_peak': 'prob',
+ 'p_e_peak': 'prob',
+}
+
+for cell_type in ['gridcell', 'not bs']:
+ for key in bins:
+ fig = plt.figure(figsize=(3.5,2.2))
+ plt.suptitle(key + ' ' + cell_type)
+ legend_lines = []
+ for color, query, label in zip(colors, queries, labels):
+ data.query(query + ' and ' + cell_type)[key].hist(
+ bins=bins[key], density=density, cumulative=cumulative, lw=lw,
+ histtype=histtype, color=color)
+ legend_lines.append(matplotlib.lines.Line2D([0], [0], color=color, lw=lw, label=label))
+ plt.xlabel(xlabel[key])
+ plt.legend(
+ handles=legend_lines,
+ bbox_to_anchor=(1.04,1), borderaxespad=0, frameon=False)
+ plt.tight_layout()
+ plt.grid(False)
+# plt.xlim(-0.05, bins[key].max() - bins[key].max()*0.02)
+ sns.despine()
+ figname = f'histogram-{key}-{cell_type}'.replace(' ', '-')
+ fig.savefig(
+ output_path / 'figures' / f'{figname}.png',
+ bbox_inches='tight', transparent=True)
+ fig.savefig(
+ output_path / 'figures' / f'{figname}.svg',
+ bbox_inches='tight', transparent=True)
+
from septum_mec.analysis.plotting import plot_bootstrap_timeseries
+
psth = pd.read_feather(output_path / 'data' / 'psth.feather')
+times = pd.read_feather(output_path / 'data' / 'times.feather')
+
times = times.T.iloc[0].values
+
cs = ['#d95f02', '#e7298a', '#993404', '#980043']
+lb = ['GC 11 Hz', 'GC 30 Hz', 'NS 11 Hz', 'NS 30 Hz']
+
fig, axs = plt.subplots(1, 2, sharex=True, sharey=True, figsize=(5,2))
+ii = 0
+for cell_type, ls in zip(['gridcell', 'not bs'], ['-', '--']):
+ for i, (ax, query) in enumerate(zip(axs.ravel(), queries)):
+ selection = [
+ f'{r.action}_{r.channel_group}_{r.unit_name}'
+ for i, r in data.query(query + ' and ' + cell_type).iterrows()]
+ values = psth.loc[:, selection].dropna(axis=1).to_numpy()
+
+ plot_bootstrap_timeseries(times, values, ax=ax, lw=2, label=lb[ii], color=cs[ii], ls=ls)
+ # ax.set_title(titles[i])
+ ax.set_xlabel('Time (s)')
+ ax.legend(frameon=False)
+ ii += 1
+ axs[0].set_ylabel('Probability density')
+ sns.despine()
+ plt.xlim(0, 0.029)
+
+figname = f'response-probability'
+fig.savefig(
+ output_path / 'figures' / f'{figname}.png',
+ bbox_inches='tight', transparent=True)
+fig.savefig(
+ output_path / 'figures' / f'{figname}.svg',
+ bbox_inches='tight', transparent=True)
+
action = project.require_action("stimulus-response")
+
\n", + " | action | \n", + "channel_group | \n", + "unit_name | \n", + "average_rate | \n", + "speed_score | \n", + "out_field_mean_rate | \n", + "in_field_mean_rate | \n", + "max_field_mean_rate | \n", + "max_rate | \n", + "sparsity | \n", + "... | \n", + "p_e_peak | \n", + "t_i_peak | \n", + "p_i_peak | \n", + "half_width | \n", + "peak_to_trough | \n", + "average_firing_rate | \n", + "bs | \n", + "bs_stim | \n", + "bs_ctrl | \n", + "gridcell | \n", + "
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
32 | \n", + "1833-260619-1 | \n", + "0 | \n", + "118 | \n", + "5.946164 | \n", + "0.169495 | \n", + "4.138169 | \n", + "10.175750 | \n", + "16.836097 | \n", + "29.863371 | \n", + "0.633240 | \n", + "... | \n", + "NaN | \n", + "NaN | \n", + "NaN | \n", + "0.272875 | \n", + "0.602667 | \n", + "5.945508 | \n", + "True | \n", + "NaN | \n", + "1.0 | \n", + "True | \n", + "
34 | \n", + "1833-260619-1 | \n", + "0 | \n", + "130 | \n", + "2.860363 | \n", + "0.081075 | \n", + "1.362852 | \n", + "6.837975 | \n", + "10.333063 | \n", + "21.846576 | \n", + "0.424446 | \n", + "... | \n", + "NaN | \n", + "NaN | \n", + "NaN | \n", + "0.226452 | \n", + "0.274814 | \n", + "2.860048 | \n", + "False | \n", + "NaN | \n", + "0.0 | \n", + "True | \n", + "
35 | \n", + "1833-260619-1 | \n", + "0 | \n", + "132 | \n", + "3.366046 | \n", + "0.072301 | \n", + "1.204876 | \n", + "8.320200 | \n", + "11.903539 | \n", + "24.820419 | \n", + "0.393028 | \n", + "... | \n", + "NaN | \n", + "NaN | \n", + "NaN | \n", + "0.247266 | \n", + "0.570104 | \n", + "3.365674 | \n", + "True | \n", + "NaN | \n", + "1.0 | \n", + "True | \n", + "
39 | \n", + "1833-260619-1 | \n", + "1 | \n", + "116 | \n", + "17.473449 | \n", + "0.193373 | \n", + "12.435315 | \n", + "25.886509 | \n", + "35.066123 | \n", + "58.438209 | \n", + "0.760804 | \n", + "... | \n", + "NaN | \n", + "NaN | \n", + "NaN | \n", + "0.284542 | \n", + "0.644111 | \n", + "17.471520 | \n", + "True | \n", + "NaN | \n", + "1.0 | \n", + "True | \n", + "
40 | \n", + "1833-260619-1 | \n", + "1 | \n", + "126 | \n", + "5.892390 | \n", + "0.183633 | \n", + "4.008668 | \n", + "10.376607 | \n", + "11.424828 | \n", + "22.616252 | \n", + "0.698596 | \n", + "... | \n", + "NaN | \n", + "NaN | \n", + "NaN | \n", + "0.259920 | \n", + "0.581698 | \n", + "5.891739 | \n", + "True | \n", + "NaN | \n", + "1.0 | \n", + "True | \n", + "
42 | \n", + "1833-260619-1 | \n", + "3 | \n", + "114 | \n", + "13.438331 | \n", + "0.224642 | \n", + "10.451118 | \n", + "18.904366 | \n", + "20.482248 | \n", + "37.829102 | \n", + "0.841781 | \n", + "... | \n", + "NaN | \n", + "NaN | \n", + "NaN | \n", + "0.263630 | \n", + "0.596746 | \n", + "13.436847 | \n", + "True | \n", + "NaN | \n", + "1.0 | \n", + "True | \n", + "
43 | \n", + "1833-260619-1 | \n", + "5 | \n", + "100 | \n", + "17.448630 | \n", + "0.144593 | \n", + "12.651420 | \n", + "25.885399 | \n", + "31.780144 | \n", + "50.983827 | \n", + "0.823859 | \n", + "... | \n", + "NaN | \n", + "NaN | \n", + "NaN | \n", + "0.281399 | \n", + "0.607354 | \n", + "17.446704 | \n", + "True | \n", + "NaN | \n", + "1.0 | \n", + "True | \n", + "
45 | \n", + "1833-260619-1 | \n", + "6 | \n", + "102 | \n", + "10.841667 | \n", + "0.235736 | \n", + "7.896926 | \n", + "16.159949 | \n", + "15.994156 | \n", + "37.844022 | \n", + "0.799767 | \n", + "... | \n", + "NaN | \n", + "NaN | \n", + "NaN | \n", + "0.279177 | \n", + "0.585152 | \n", + "10.840470 | \n", + "True | \n", + "NaN | \n", + "1.0 | \n", + "True | \n", + "
48 | \n", + "1833-260619-1 | \n", + "6 | \n", + "112 | \n", + "5.891356 | \n", + "0.226892 | \n", + "4.028409 | \n", + "10.441355 | \n", + "13.169649 | \n", + "24.406383 | \n", + "0.643995 | \n", + "... | \n", + "NaN | \n", + "NaN | \n", + "NaN | \n", + "0.282336 | \n", + "0.711705 | \n", + "5.890705 | \n", + "True | \n", + "NaN | \n", + "1.0 | \n", + "True | \n", + "
49 | \n", + "1833-260619-1 | \n", + "6 | \n", + "124 | \n", + "7.915120 | \n", + "0.182376 | \n", + "4.543545 | \n", + "14.013583 | \n", + "17.035745 | \n", + "30.787249 | \n", + "0.646322 | \n", + "... | \n", + "NaN | \n", + "NaN | \n", + "NaN | \n", + "0.285816 | \n", + "0.603160 | \n", + "7.914246 | \n", + "True | \n", + "NaN | \n", + "1.0 | \n", + "True | \n", + "
57 | \n", + "1834-150319-3 | \n", + "3 | \n", + "61 | \n", + "17.163920 | \n", + "0.021890 | \n", + "12.070353 | \n", + "23.188083 | \n", + "24.427655 | \n", + "44.829894 | \n", + "0.837844 | \n", + "... | \n", + "NaN | \n", + "NaN | \n", + "NaN | \n", + "0.277867 | \n", + "0.588852 | \n", + "17.162446 | \n", + "True | \n", + "NaN | \n", + "1.0 | \n", + "True | \n", + "
124 | \n", + "1833-010719-1 | \n", + "1 | \n", + "219 | \n", + "2.868256 | \n", + "0.170572 | \n", + "1.391229 | \n", + "6.759410 | \n", + "8.941986 | \n", + "21.915347 | \n", + "0.446442 | \n", + "... | \n", + "NaN | \n", + "NaN | \n", + "NaN | \n", + "0.271262 | \n", + "0.615002 | \n", + "2.868000 | \n", + "True | \n", + "NaN | \n", + "1.0 | \n", + "True | \n", + "
125 | \n", + "1833-010719-1 | \n", + "1 | \n", + "221 | \n", + "6.912671 | \n", + "0.090486 | \n", + "4.070879 | \n", + "11.915337 | \n", + "24.220877 | \n", + "32.274461 | \n", + "0.661683 | \n", + "... | \n", + "NaN | \n", + "NaN | \n", + "NaN | \n", + "0.307694 | \n", + "0.659653 | \n", + "6.912052 | \n", + "True | \n", + "NaN | \n", + "1.0 | \n", + "True | \n", + "
126 | \n", + "1833-010719-1 | \n", + "1 | \n", + "229 | \n", + "4.230245 | \n", + "0.018811 | \n", + "1.546702 | \n", + "8.504585 | \n", + "15.581766 | \n", + "33.782863 | \n", + "0.456739 | \n", + "... | \n", + "NaN | \n", + "NaN | \n", + "NaN | \n", + "0.267708 | \n", + "0.630543 | \n", + "4.229867 | \n", + "True | \n", + "NaN | \n", + "1.0 | \n", + "True | \n", + "
128 | \n", + "1833-010719-1 | \n", + "1 | \n", + "8 | \n", + "16.737459 | \n", + "0.254297 | \n", + "12.420895 | \n", + "25.377508 | \n", + "23.273238 | \n", + "52.301684 | \n", + "0.802417 | \n", + "... | \n", + "NaN | \n", + "NaN | \n", + "NaN | \n", + "0.289100 | \n", + "0.673221 | \n", + "16.735961 | \n", + "True | \n", + "NaN | \n", + "1.0 | \n", + "True | \n", + "
129 | \n", + "1833-010719-1 | \n", + "2 | \n", + "202 | \n", + "25.977054 | \n", + "0.226032 | \n", + "21.598716 | \n", + "37.463629 | \n", + "43.547728 | \n", + "66.169116 | \n", + "0.862176 | \n", + "... | \n", + "NaN | \n", + "NaN | \n", + "NaN | \n", + "0.290402 | \n", + "0.650772 | \n", + "25.974728 | \n", + "True | \n", + "NaN | \n", + "1.0 | \n", + "True | \n", + "
131 | \n", + "1833-010719-1 | \n", + "3 | \n", + "171 | \n", + "14.687550 | \n", + "0.163959 | \n", + "11.038136 | \n", + "20.488701 | \n", + "21.342234 | \n", + "45.144706 | \n", + "0.858017 | \n", + "... | \n", + "NaN | \n", + "NaN | \n", + "NaN | \n", + "0.272160 | \n", + "0.620429 | \n", + "14.686236 | \n", + "True | \n", + "NaN | \n", + "1.0 | \n", + "True | \n", + "
132 | \n", + "1833-010719-1 | \n", + "3 | \n", + "198 | \n", + "18.659249 | \n", + "0.282318 | \n", + "15.427596 | \n", + "26.715844 | \n", + "33.932272 | \n", + "51.441681 | \n", + "0.860475 | \n", + "... | \n", + "NaN | \n", + "NaN | \n", + "NaN | \n", + "0.241405 | \n", + "0.595513 | \n", + "18.657578 | \n", + "True | \n", + "NaN | \n", + "1.0 | \n", + "True | \n", + "
134 | \n", + "1833-010719-1 | \n", + "3 | \n", + "240 | \n", + "3.107182 | \n", + "0.076765 | \n", + "1.059941 | \n", + "7.228602 | \n", + "12.831970 | \n", + "33.059125 | \n", + "0.383354 | \n", + "... | \n", + "NaN | \n", + "NaN | \n", + "NaN | \n", + "0.269911 | \n", + "0.609574 | \n", + "3.106903 | \n", + "True | \n", + "NaN | \n", + "1.0 | \n", + "True | \n", + "
135 | \n", + "1833-010719-1 | \n", + "5 | \n", + "134 | \n", + "6.214363 | \n", + "0.168450 | \n", + "4.835608 | \n", + "9.832902 | \n", + "18.534635 | \n", + "33.761835 | \n", + "0.750893 | \n", + "... | \n", + "NaN | \n", + "NaN | \n", + "NaN | \n", + "0.273069 | \n", + "0.651265 | \n", + "6.213807 | \n", + "True | \n", + "NaN | \n", + "1.0 | \n", + "True | \n", + "
136 | \n", + "1833-010719-1 | \n", + "5 | \n", + "144 | \n", + "2.226506 | \n", + "0.119543 | \n", + "1.188425 | \n", + "5.927293 | \n", + "13.273928 | \n", + "26.877971 | \n", + "0.358918 | \n", + "... | \n", + "NaN | \n", + "NaN | \n", + "NaN | \n", + "0.263251 | \n", + "0.629310 | \n", + "2.226306 | \n", + "True | \n", + "NaN | \n", + "1.0 | \n", + "True | \n", + "
209 | \n", + "1833-050619-1 | \n", + "2 | \n", + "99 | \n", + "3.350056 | \n", + "0.095012 | \n", + "1.224499 | \n", + "7.669547 | \n", + "14.470606 | \n", + "29.613931 | \n", + "0.384212 | \n", + "... | \n", + "NaN | \n", + "NaN | \n", + "NaN | \n", + "0.251027 | \n", + "0.593786 | \n", + "3.347881 | \n", + "True | \n", + "NaN | \n", + "1.0 | \n", + "True | \n", + "
214 | \n", + "1833-050619-1 | \n", + "6 | \n", + "60 | \n", + "7.177620 | \n", + "0.259306 | \n", + "5.263129 | \n", + "11.558126 | \n", + "13.097257 | \n", + "24.533320 | \n", + "0.764622 | \n", + "... | \n", + "NaN | \n", + "NaN | \n", + "NaN | \n", + "0.296577 | \n", + "0.631283 | \n", + "7.172961 | \n", + "True | \n", + "NaN | \n", + "1.0 | \n", + "True | \n", + "
215 | \n", + "1833-050619-1 | \n", + "6 | \n", + "64 | \n", + "16.944449 | \n", + "0.243525 | \n", + "13.371230 | \n", + "26.025889 | \n", + "33.591762 | \n", + "60.449939 | \n", + "0.824103 | \n", + "... | \n", + "NaN | \n", + "NaN | \n", + "NaN | \n", + "0.295235 | \n", + "0.633010 | \n", + "16.933450 | \n", + "True | \n", + "NaN | \n", + "1.0 | \n", + "True | \n", + "
216 | \n", + "1833-050619-1 | \n", + "6 | \n", + "91 | \n", + "3.325889 | \n", + "0.155904 | \n", + "2.039584 | \n", + "7.702821 | \n", + "9.078369 | \n", + "21.975777 | \n", + "0.462461 | \n", + "... | \n", + "NaN | \n", + "NaN | \n", + "NaN | \n", + "0.268553 | \n", + "0.618949 | \n", + "3.323730 | \n", + "True | \n", + "NaN | \n", + "1.0 | \n", + "True | \n", + "
221 | \n", + "1833-060619-1 | \n", + "4 | \n", + "172 | \n", + "2.654829 | \n", + "0.119661 | \n", + "1.666324 | \n", + "6.169001 | \n", + "7.323174 | \n", + "22.931784 | \n", + "0.457083 | \n", + "... | \n", + "NaN | \n", + "NaN | \n", + "NaN | \n", + "0.263816 | \n", + "0.607601 | \n", + "2.654511 | \n", + "True | \n", + "NaN | \n", + "1.0 | \n", + "True | \n", + "
223 | \n", + "1833-060619-1 | \n", + "5 | \n", + "164 | \n", + "3.083686 | \n", + "0.021853 | \n", + "1.755081 | \n", + "5.101697 | \n", + "8.325821 | \n", + "21.146134 | \n", + "0.566049 | \n", + "... | \n", + "NaN | \n", + "NaN | \n", + "NaN | \n", + "0.313833 | \n", + "0.646825 | \n", + "3.083316 | \n", + "True | \n", + "NaN | \n", + "1.0 | \n", + "True | \n", + "
227 | \n", + "1833-060619-1 | \n", + "6 | \n", + "170 | \n", + "3.080462 | \n", + "0.155454 | \n", + "1.816201 | \n", + "6.197439 | \n", + "8.744690 | \n", + "18.172981 | \n", + "0.529688 | \n", + "... | \n", + "NaN | \n", + "NaN | \n", + "NaN | \n", + "0.261029 | \n", + "0.596500 | \n", + "3.080092 | \n", + "True | \n", + "NaN | \n", + "1.0 | \n", + "True | \n", + "
262 | \n", + "1834-150319-1 | \n", + "3 | \n", + "95 | \n", + "19.609185 | \n", + "0.063354 | \n", + "14.334866 | \n", + "25.933220 | \n", + "29.106613 | \n", + "53.460587 | \n", + "0.857509 | \n", + "... | \n", + "NaN | \n", + "NaN | \n", + "NaN | \n", + "0.282343 | \n", + "0.604147 | \n", + "19.498454 | \n", + "True | \n", + "NaN | \n", + "1.0 | \n", + "True | \n", + "
274 | \n", + "1839-120619-1 | \n", + "5 | \n", + "158 | \n", + "12.579822 | \n", + "0.285708 | \n", + "9.656518 | \n", + "23.105339 | \n", + "25.311402 | \n", + "59.566964 | \n", + "0.660943 | \n", + "... | \n", + "NaN | \n", + "NaN | \n", + "NaN | \n", + "0.265655 | \n", + "0.574791 | \n", + "12.578109 | \n", + "True | \n", + "NaN | \n", + "1.0 | \n", + "True | \n", + "
... | \n", + "... | \n", + "... | \n", + "... | \n", + "... | \n", + "... | \n", + "... | \n", + "... | \n", + "... | \n", + "... | \n", + "... | \n", + "... | \n", + "... | \n", + "... | \n", + "... | \n", + "... | \n", + "... | \n", + "... | \n", + "... | \n", + "... | \n", + "... | \n", + "... | \n", + "
1130 | \n", + "1834-010319-4 | \n", + "0 | \n", + "7 | \n", + "18.428099 | \n", + "0.073675 | \n", + "13.995565 | \n", + "25.034061 | \n", + "27.551569 | \n", + "45.574876 | \n", + "0.864388 | \n", + "... | \n", + "NaN | \n", + "NaN | \n", + "NaN | \n", + "0.284016 | \n", + "0.615742 | \n", + "18.426477 | \n", + "True | \n", + "NaN | \n", + "1.0 | \n", + "True | \n", + "
1151 | \n", + "1833-200619-1 | \n", + "4 | \n", + "165 | \n", + "4.093726 | \n", + "0.112030 | \n", + "1.560769 | \n", + "9.952907 | \n", + "16.871964 | \n", + "34.400735 | \n", + "0.371794 | \n", + "... | \n", + "NaN | \n", + "NaN | \n", + "NaN | \n", + "0.272936 | \n", + "0.784972 | \n", + "4.093056 | \n", + "True | \n", + "NaN | \n", + "1.0 | \n", + "True | \n", + "
1152 | \n", + "1833-200619-1 | \n", + "6 | \n", + "163 | \n", + "17.705502 | \n", + "0.202908 | \n", + "14.631392 | \n", + "24.895637 | \n", + "34.144570 | \n", + "51.462522 | \n", + "0.877996 | \n", + "... | \n", + "NaN | \n", + "NaN | \n", + "NaN | \n", + "0.303012 | \n", + "0.661133 | \n", + "17.702603 | \n", + "True | \n", + "NaN | \n", + "1.0 | \n", + "True | \n", + "
1153 | \n", + "1833-200619-1 | \n", + "6 | \n", + "171 | \n", + "4.061107 | \n", + "0.058014 | \n", + "1.879235 | \n", + "7.260758 | \n", + "11.252257 | \n", + "20.574695 | \n", + "0.561983 | \n", + "... | \n", + "NaN | \n", + "NaN | \n", + "NaN | \n", + "0.310060 | \n", + "0.632763 | \n", + "4.060442 | \n", + "True | \n", + "NaN | \n", + "1.0 | \n", + "True | \n", + "
1154 | \n", + "1833-200619-1 | \n", + "6 | \n", + "206 | \n", + "3.982277 | \n", + "0.150630 | \n", + "2.316705 | \n", + "7.168058 | \n", + "9.286450 | \n", + "19.626376 | \n", + "0.618229 | \n", + "... | \n", + "NaN | \n", + "NaN | \n", + "NaN | \n", + "0.290294 | \n", + "0.618949 | \n", + "3.981625 | \n", + "True | \n", + "NaN | \n", + "1.0 | \n", + "True | \n", + "
1155 | \n", + "1833-200619-1 | \n", + "6 | \n", + "240 | \n", + "4.089649 | \n", + "0.098818 | \n", + "1.539874 | \n", + "10.560745 | \n", + "15.374288 | \n", + "32.783007 | \n", + "0.358157 | \n", + "... | \n", + "NaN | \n", + "NaN | \n", + "NaN | \n", + "0.263375 | \n", + "0.622896 | \n", + "4.088979 | \n", + "True | \n", + "NaN | \n", + "1.0 | \n", + "True | \n", + "
1156 | \n", + "1833-200619-1 | \n", + "7 | \n", + "143 | \n", + "9.300587 | \n", + "0.218310 | \n", + "6.750717 | \n", + "13.150023 | \n", + "13.197378 | \n", + "25.067697 | \n", + "0.825910 | \n", + "... | \n", + "NaN | \n", + "NaN | \n", + "NaN | \n", + "0.289628 | \n", + "0.650032 | \n", + "9.299064 | \n", + "True | \n", + "NaN | \n", + "1.0 | \n", + "True | \n", + "
1162 | \n", + "1839-120619-3 | \n", + "5 | \n", + "131 | \n", + "17.773050 | \n", + "0.076020 | \n", + "9.779864 | \n", + "29.707618 | \n", + "42.215165 | \n", + "77.486029 | \n", + "0.651012 | \n", + "... | \n", + "NaN | \n", + "NaN | \n", + "NaN | \n", + "0.245031 | \n", + "0.528413 | \n", + "17.770859 | \n", + "True | \n", + "NaN | \n", + "1.0 | \n", + "True | \n", + "
1165 | \n", + "1839-120619-3 | \n", + "6 | \n", + "133 | \n", + "2.612293 | \n", + "0.053873 | \n", + "1.055067 | \n", + "6.992168 | \n", + "9.603099 | \n", + "17.060484 | \n", + "0.372375 | \n", + "... | \n", + "NaN | \n", + "NaN | \n", + "NaN | \n", + "0.239301 | \n", + "0.531126 | \n", + "2.611971 | \n", + "True | \n", + "NaN | \n", + "1.0 | \n", + "True | \n", + "
1167 | \n", + "1839-120619-3 | \n", + "7 | \n", + "119 | \n", + "4.950355 | \n", + "0.132893 | \n", + "3.636504 | \n", + "7.175598 | \n", + "7.291281 | \n", + "14.571674 | \n", + "0.836244 | \n", + "... | \n", + "NaN | \n", + "NaN | \n", + "NaN | \n", + "0.284221 | \n", + "0.610068 | \n", + "4.949745 | \n", + "True | \n", + "NaN | \n", + "1.0 | \n", + "True | \n", + "
1168 | \n", + "1839-120619-3 | \n", + "7 | \n", + "127 | \n", + "5.407801 | \n", + "0.091931 | \n", + "3.251329 | \n", + "15.356306 | \n", + "18.617758 | \n", + "37.590469 | \n", + "0.414271 | \n", + "... | \n", + "NaN | \n", + "NaN | \n", + "NaN | \n", + "0.273572 | \n", + "0.611548 | \n", + "5.407135 | \n", + "True | \n", + "NaN | \n", + "1.0 | \n", + "True | \n", + "
1199 | \n", + "1833-260619-3 | \n", + "0 | \n", + "140 | \n", + "3.564682 | \n", + "0.063184 | \n", + "2.498756 | \n", + "5.782665 | \n", + "8.770230 | \n", + "17.134986 | \n", + "0.720704 | \n", + "... | \n", + "NaN | \n", + "NaN | \n", + "NaN | \n", + "0.189559 | \n", + "0.248665 | \n", + "3.564358 | \n", + "False | \n", + "NaN | \n", + "0.0 | \n", + "True | \n", + "
1200 | \n", + "1833-260619-3 | \n", + "0 | \n", + "141 | \n", + "2.694224 | \n", + "0.094154 | \n", + "1.691471 | \n", + "5.502054 | \n", + "10.395725 | \n", + "20.328752 | \n", + "0.519950 | \n", + "... | \n", + "NaN | \n", + "NaN | \n", + "NaN | \n", + "0.225575 | \n", + "0.277528 | \n", + "2.693978 | \n", + "False | \n", + "NaN | \n", + "0.0 | \n", + "True | \n", + "
1202 | \n", + "1833-260619-3 | \n", + "0 | \n", + "182 | \n", + "5.289030 | \n", + "0.148720 | \n", + "3.342163 | \n", + "10.892485 | \n", + "16.803801 | \n", + "30.523793 | \n", + "0.544679 | \n", + "... | \n", + "NaN | \n", + "NaN | \n", + "NaN | \n", + "0.275930 | \n", + "0.594526 | \n", + "5.288548 | \n", + "True | \n", + "NaN | \n", + "1.0 | \n", + "True | \n", + "
1203 | \n", + "1833-260619-3 | \n", + "0 | \n", + "194 | \n", + "6.485358 | \n", + "0.096207 | \n", + "3.706339 | \n", + "12.069498 | \n", + "18.212336 | \n", + "29.243464 | \n", + "0.590584 | \n", + "... | \n", + "NaN | \n", + "NaN | \n", + "NaN | \n", + "0.222604 | \n", + "0.576271 | \n", + "6.484767 | \n", + "True | \n", + "NaN | \n", + "1.0 | \n", + "True | \n", + "
1205 | \n", + "1833-260619-3 | \n", + "0 | \n", + "209 | \n", + "3.425497 | \n", + "0.085117 | \n", + "1.306754 | \n", + "8.551145 | \n", + "11.161798 | \n", + "29.652423 | \n", + "0.378044 | \n", + "... | \n", + "NaN | \n", + "NaN | \n", + "NaN | \n", + "0.244049 | \n", + "0.571337 | \n", + "3.425185 | \n", + "True | \n", + "NaN | \n", + "1.0 | \n", + "True | \n", + "
1207 | \n", + "1833-260619-3 | \n", + "1 | \n", + "170 | \n", + "26.841716 | \n", + "0.218178 | \n", + "22.328079 | \n", + "38.090240 | \n", + "50.981983 | \n", + "74.601637 | \n", + "0.857579 | \n", + "... | \n", + "NaN | \n", + "NaN | \n", + "NaN | \n", + "0.257469 | \n", + "0.636957 | \n", + "26.839270 | \n", + "True | \n", + "NaN | \n", + "1.0 | \n", + "True | \n", + "
1208 | \n", + "1833-260619-3 | \n", + "1 | \n", + "207 | \n", + "4.589791 | \n", + "0.088439 | \n", + "2.309667 | \n", + "8.938164 | \n", + "10.731362 | \n", + "25.229471 | \n", + "0.538208 | \n", + "... | \n", + "NaN | \n", + "NaN | \n", + "NaN | \n", + "0.252255 | \n", + "0.587372 | \n", + "4.589373 | \n", + "True | \n", + "NaN | \n", + "1.0 | \n", + "True | \n", + "
1211 | \n", + "1833-260619-3 | \n", + "3 | \n", + "176 | \n", + "7.407735 | \n", + "0.156101 | \n", + "5.622472 | \n", + "11.694017 | \n", + "16.474141 | \n", + "32.870310 | \n", + "0.757528 | \n", + "... | \n", + "NaN | \n", + "NaN | \n", + "NaN | \n", + "0.261129 | \n", + "0.592306 | \n", + "7.407060 | \n", + "True | \n", + "NaN | \n", + "1.0 | \n", + "True | \n", + "
1213 | \n", + "1833-260619-3 | \n", + "5 | \n", + "111 | \n", + "9.222663 | \n", + "0.179913 | \n", + "6.341652 | \n", + "14.990045 | \n", + "17.803066 | \n", + "32.423819 | \n", + "0.732917 | \n", + "... | \n", + "NaN | \n", + "NaN | \n", + "NaN | \n", + "0.277189 | \n", + "0.615988 | \n", + "9.221822 | \n", + "True | \n", + "NaN | \n", + "1.0 | \n", + "True | \n", + "
1216 | \n", + "1833-260619-3 | \n", + "6 | \n", + "142 | \n", + "9.359639 | \n", + "0.129023 | \n", + "6.738758 | \n", + "14.564994 | \n", + "20.758052 | \n", + "44.189302 | \n", + "0.773930 | \n", + "... | \n", + "NaN | \n", + "NaN | \n", + "NaN | \n", + "0.300175 | \n", + "0.610068 | \n", + "9.358786 | \n", + "True | \n", + "NaN | \n", + "1.0 | \n", + "True | \n", + "
1218 | \n", + "1833-260619-3 | \n", + "6 | \n", + "192 | \n", + "7.836336 | \n", + "0.170862 | \n", + "4.889011 | \n", + "13.019928 | \n", + "17.648343 | \n", + "34.791219 | \n", + "0.715811 | \n", + "... | \n", + "NaN | \n", + "NaN | \n", + "NaN | \n", + "0.287132 | \n", + "0.616235 | \n", + "7.835622 | \n", + "True | \n", + "NaN | \n", + "1.0 | \n", + "True | \n", + "
1222 | \n", + "1833-200619-3 | \n", + "0 | \n", + "91 | \n", + "7.072750 | \n", + "0.074100 | \n", + "4.679924 | \n", + "11.282597 | \n", + "18.578196 | \n", + "35.109099 | \n", + "0.713088 | \n", + "... | \n", + "NaN | \n", + "NaN | \n", + "NaN | \n", + "0.293775 | \n", + "0.657679 | \n", + "7.071948 | \n", + "True | \n", + "NaN | \n", + "1.0 | \n", + "True | \n", + "
1228 | \n", + "1833-200619-3 | \n", + "3 | \n", + "82 | \n", + "15.697615 | \n", + "0.127761 | \n", + "12.267443 | \n", + "21.346293 | \n", + "27.567344 | \n", + "38.706425 | \n", + "0.874674 | \n", + "... | \n", + "NaN | \n", + "NaN | \n", + "NaN | \n", + "0.252895 | \n", + "0.600200 | \n", + "15.695836 | \n", + "True | \n", + "NaN | \n", + "1.0 | \n", + "True | \n", + "
1229 | \n", + "1833-200619-3 | \n", + "4 | \n", + "113 | \n", + "11.770313 | \n", + "0.136640 | \n", + "6.835310 | \n", + "20.280536 | \n", + "22.248766 | \n", + "44.143227 | \n", + "0.676058 | \n", + "... | \n", + "NaN | \n", + "NaN | \n", + "NaN | \n", + "0.271023 | \n", + "0.699617 | \n", + "11.768979 | \n", + "True | \n", + "NaN | \n", + "1.0 | \n", + "True | \n", + "
1231 | \n", + "1833-200619-3 | \n", + "5 | \n", + "59 | \n", + "4.442527 | \n", + "0.110165 | \n", + "2.926793 | \n", + "7.344323 | \n", + "8.786494 | \n", + "20.320606 | \n", + "0.722984 | \n", + "... | \n", + "NaN | \n", + "NaN | \n", + "NaN | \n", + "0.343906 | \n", + "0.698383 | \n", + "4.442023 | \n", + "True | \n", + "NaN | \n", + "1.0 | \n", + "True | \n", + "
1232 | \n", + "1833-200619-3 | \n", + "6 | \n", + "120 | \n", + "22.461229 | \n", + "0.268466 | \n", + "18.182326 | \n", + "32.115585 | \n", + "33.640870 | \n", + "62.235139 | \n", + "0.833921 | \n", + "... | \n", + "NaN | \n", + "NaN | \n", + "NaN | \n", + "0.294291 | \n", + "0.639177 | \n", + "22.458685 | \n", + "True | \n", + "NaN | \n", + "1.0 | \n", + "True | \n", + "
1233 | \n", + "1833-200619-3 | \n", + "6 | \n", + "126 | \n", + "3.102942 | \n", + "0.090727 | \n", + "1.447857 | \n", + "6.981766 | \n", + "9.945472 | \n", + "21.048478 | \n", + "0.436204 | \n", + "... | \n", + "NaN | \n", + "NaN | \n", + "NaN | \n", + "0.304748 | \n", + "0.641151 | \n", + "3.102590 | \n", + "True | \n", + "NaN | \n", + "1.0 | \n", + "True | \n", + "
1234 | \n", + "1833-200619-3 | \n", + "6 | \n", + "132 | \n", + "6.901437 | \n", + "0.072648 | \n", + "4.231220 | \n", + "14.073295 | \n", + "20.697950 | \n", + "36.231604 | \n", + "0.612146 | \n", + "... | \n", + "NaN | \n", + "NaN | \n", + "NaN | \n", + "0.277708 | \n", + "0.585645 | \n", + "6.900656 | \n", + "True | \n", + "NaN | \n", + "1.0 | \n", + "True | \n", + "
1235 | \n", + "1833-200619-3 | \n", + "6 | \n", + "150 | \n", + "3.767582 | \n", + "0.114920 | \n", + "1.422876 | \n", + "10.607271 | \n", + "13.651769 | \n", + "34.348592 | \n", + "0.332963 | \n", + "... | \n", + "NaN | \n", + "NaN | \n", + "NaN | \n", + "0.258204 | \n", + "0.608094 | \n", + "3.767155 | \n", + "True | \n", + "NaN | \n", + "1.0 | \n", + "True | \n", + "
130 rows × 51 columns
\n", + "