f64 commited on
Commit
744380c
·
1 Parent(s): 2f89b0d
Files changed (3) hide show
  1. my_static_methods.py +0 -1
  2. pages/2_TECT_IDXYZ.py +5 -4
  3. static/test.ipynb +121 -91
my_static_methods.py CHANGED
@@ -133,7 +133,6 @@ def GetClassifier(lstDfOriginal, nHystorySteps) :
133
  time_elapsed = time.time() - start2
134
  y_pred = classifierObject.predict(x_train_vect)
135
  df_train[f"predict_{fieldY}"] = y_pred
136
- print(f"{time_elapsed=}")
137
  return (classifierObject, df_train, time_elapsed)
138
 
139
  #
 
133
  time_elapsed = time.time() - start2
134
  y_pred = classifierObject.predict(x_train_vect)
135
  df_train[f"predict_{fieldY}"] = y_pred
 
136
  return (classifierObject, df_train, time_elapsed)
137
 
138
  #
pages/2_TECT_IDXYZ.py CHANGED
@@ -30,7 +30,7 @@ dictTestFilesIdXyz = {f.upper().replace("ID_XYZ/",""): f.upper() for f in lstRep
30
  @st.cache_data
31
  def GetListOf_XYZV_ToTrainClassifier(repo):
32
  lstRepoZipFiles = ["TrainData_1504_AB_gaziev.zip","TestData_1504_AB_gaziev.zip","TestData3_2204_noAB_gaziev.zip"]
33
- dictTrainThreeDataframes = my_stm.load_dataframes_from_hf(REPO, lstRepoZipFiles)
34
  lstDfOriginal = [my_stm.df_process_v_column(df) for df in dictTrainThreeDataframes.values()]
35
  return lstDfOriginal
36
 
@@ -75,7 +75,7 @@ with st.container():
75
  cols1 = st.columns([1,12], vertical_alignment="center")
76
  strBanner = "🔮 проверка предсказаний по пакетам ID_XYZ. \n 📜 формат CSV. \n 🧊 названия столбцов ID;X;Y;Z. \n 📐 размер пакетов одинаковый."
77
  cols1[0].popover("❓", help=strBanner).markdown(DescriptionMarkdown())
78
- cols1[1].info(strBanner)
79
 
80
  #col1, col2 = st.columns([2,5])
81
  col1, col2 = st.columns([4,2])
@@ -139,14 +139,15 @@ if selectedFile is not None:
139
  pack_size = list(set(dgID.apply(len)))[0]
140
  lstDfOriginal = GetListOf_XYZV_ToTrainClassifier(REPO)
141
  #classifier_object, df_train_with_predict, time_elapsed = my_stm.GetClassifier(lstDfOriginal, pack_size-1)
142
- classifier_object = GetCachedClassifier(lstDfOriginal, pack_size-1)
143
  col2.popover(type(classifier_object).__name__).write(type(classifier_object))
144
  # прогноз на обучающей выборке
145
  #columns_xyzv = [c for c in df_train_with_predict.columns if "Vis" in c] + [c for c in df_train_with_predict.columns if c[0] in "XYZ"]
146
  #col2.dataframe(df_train_with_predict[columns_xyzv], height=650)
147
  # расчет пакетов
148
  xyz = ["X","Y","Z"]
149
- df_packs_reshaped = dgID.apply(lambda df: pd.Series(df[xyz].values[::-1].reshape(1,-1)[0])).reset_index()
 
150
  x_test_vect = df_packs_reshaped.iloc[:,1:]
151
  df_packs_reshaped["Прогноз_V"] = classifier_object.predict(x_test_vect.values)
152
  col2.dataframe(df_packs_reshaped[["ID","Прогноз_V"]], height=620)
 
30
  @st.cache_data
31
  def GetListOf_XYZV_ToTrainClassifier(repo):
32
  lstRepoZipFiles = ["TrainData_1504_AB_gaziev.zip","TestData_1504_AB_gaziev.zip","TestData3_2204_noAB_gaziev.zip"]
33
+ dictTrainThreeDataframes = my_stm.load_dataframes_from_hf(repo, lstRepoZipFiles)
34
  lstDfOriginal = [my_stm.df_process_v_column(df) for df in dictTrainThreeDataframes.values()]
35
  return lstDfOriginal
36
 
 
75
  cols1 = st.columns([1,12], vertical_alignment="center")
76
  strBanner = "🔮 проверка предсказаний по пакетам ID_XYZ. \n 📜 формат CSV. \n 🧊 названия столбцов ID;X;Y;Z. \n 📐 размер пакетов одинаковый."
77
  cols1[0].popover("❓", help=strBanner).markdown(DescriptionMarkdown())
78
+ cols1[1].info("🔮 проверка предсказаний V по пакетам ID;X;Y;Z")
79
 
80
  #col1, col2 = st.columns([2,5])
81
  col1, col2 = st.columns([4,2])
 
139
  pack_size = list(set(dgID.apply(len)))[0]
140
  lstDfOriginal = GetListOf_XYZV_ToTrainClassifier(REPO)
141
  #classifier_object, df_train_with_predict, time_elapsed = my_stm.GetClassifier(lstDfOriginal, pack_size-1)
142
+ classifier_object = GetCachedClassifier(lstDfOriginal, pack_size-1) # сделал закэшированную версию
143
  col2.popover(type(classifier_object).__name__).write(type(classifier_object))
144
  # прогноз на обучающей выборке
145
  #columns_xyzv = [c for c in df_train_with_predict.columns if "Vis" in c] + [c for c in df_train_with_predict.columns if c[0] in "XYZ"]
146
  #col2.dataframe(df_train_with_predict[columns_xyzv], height=650)
147
  # расчет пакетов
148
  xyz = ["X","Y","Z"]
149
+ df_packs_reshaped = dgID.apply(lambda df: pd.Series(df[xyz].values[::-1].reshape(1,-1)[0])).reset_index() # правильный порядок
150
+ #df_packs_reshaped = dgID.apply(lambda df: pd.Series(df[xyz].values.reshape(1,-1)[0])).reset_index() # тестовый порядок xyz наоборот
151
  x_test_vect = df_packs_reshaped.iloc[:,1:]
152
  df_packs_reshaped["Прогноз_V"] = classifier_object.predict(x_test_vect.values)
153
  col2.dataframe(df_packs_reshaped[["ID","Прогноз_V"]], height=620)
static/test.ipynb CHANGED
@@ -2,12 +2,12 @@
2
  "cells": [
3
  {
4
  "cell_type": "code",
5
- "execution_count": 33,
6
  "metadata": {},
7
  "outputs": [],
8
  "source": [
9
  "#@title IMPORT\n",
10
- "import io,os,re,sys,math,time,uuid,ctypes,pickle,psutil,random,shutil,string,urllib,decimal,datetime,itertools,traceback,collections\n",
11
  "import matplotlib.pyplot as plt, seaborn as sns, plotly.express as px\n",
12
  "import numpy as np, pandas as pd\n",
13
  "\n",
@@ -16,7 +16,7 @@
16
  },
17
  {
18
  "cell_type": "code",
19
- "execution_count": 34,
20
  "metadata": {},
21
  "outputs": [
22
  {
@@ -25,7 +25,7 @@
25
  "text": [
26
  "<>:1: SyntaxWarning: invalid escape sequence '\\M'\n",
27
  "<>:1: SyntaxWarning: invalid escape sequence '\\M'\n",
28
- "C:\\Users\\f64\\AppData\\Local\\Temp\\ipykernel_36416\\1255343956.py:1: SyntaxWarning: invalid escape sequence '\\M'\n",
29
  " path1 = \"N:\\Makarov\\Development\\Python\\Jupiter Notebooks\\Gaziev CSV\\TestData_1504_AB_soloV_gaziev.zip\"\n"
30
  ]
31
  },
@@ -228,7 +228,7 @@
228
  "[12010 rows x 10 columns]"
229
  ]
230
  },
231
- "execution_count": 34,
232
  "metadata": {},
233
  "output_type": "execute_result"
234
  }
@@ -249,7 +249,7 @@
249
  },
250
  {
251
  "cell_type": "code",
252
- "execution_count": 35,
253
  "metadata": {},
254
  "outputs": [
255
  {
@@ -270,7 +270,7 @@
270
  },
271
  {
272
  "cell_type": "code",
273
- "execution_count": 36,
274
  "metadata": {},
275
  "outputs": [
276
  {
@@ -437,7 +437,7 @@
437
  "18 AAA011113 21 392 -205"
438
  ]
439
  },
440
- "execution_count": 36,
441
  "metadata": {},
442
  "output_type": "execute_result"
443
  }
@@ -456,7 +456,7 @@
456
  },
457
  {
458
  "cell_type": "code",
459
- "execution_count": 38,
460
  "metadata": {},
461
  "outputs": [
462
  {
@@ -470,9 +470,9 @@
470
  "name": "stderr",
471
  "output_type": "stream",
472
  "text": [
473
- "C:\\Users\\f64\\AppData\\Local\\Temp\\ipykernel_36416\\1846308829.py:2: DeprecationWarning: DataFrameGroupBy.apply operated on the grouping columns. This behavior is deprecated, and in a future version of pandas the grouping columns will be excluded from the operation. Either pass `include_groups=False` to exclude the groupings or explicitly select the grouping columns after groupby to silence this warning.\n",
474
  " print(f\"{set(dgID.apply(len))=}\")\n",
475
- "C:\\Users\\f64\\AppData\\Local\\Temp\\ipykernel_36416\\1846308829.py:4: DeprecationWarning: DataFrameGroupBy.apply operated on the grouping columns. This behavior is deprecated, and in a future version of pandas the grouping columns will be excluded from the operation. Either pass `include_groups=False` to exclude the groupings or explicitly select the grouping columns after groupby to silence this warning.\n",
476
  " dgID.apply(len).reset_index()\n"
477
  ]
478
  },
@@ -630,7 +630,7 @@
630
  "19 DDD011113 7"
631
  ]
632
  },
633
- "execution_count": 38,
634
  "metadata": {},
635
  "output_type": "execute_result"
636
  }
@@ -644,15 +644,13 @@
644
  },
645
  {
646
  "cell_type": "code",
647
- "execution_count": null,
648
  "metadata": {},
649
  "outputs": [
650
  {
651
  "name": "stdout",
652
  "output_type": "stream",
653
  "text": [
654
- "[['-221' '575' '438' '-102' '601' '258' '-220' '561' '-13' '113' '567'\n",
655
- " '-242' '221' '581' '-249' '222' '598' '-85' '-300' '554' '-130']]\n",
656
  "[['-300' '554' '-130' '222' '598' '-85' '221' '581' '-249' '113' '567'\n",
657
  " '-242' '-220' '561' '-13' '-102' '601' '258' '-221' '575' '438']]\n"
658
  ]
@@ -749,7 +747,7 @@
749
  "119 BBB011117 -300 554 -130"
750
  ]
751
  },
752
- "execution_count": 32,
753
  "metadata": {},
754
  "output_type": "execute_result"
755
  }
@@ -768,15 +766,15 @@
768
  },
769
  {
770
  "cell_type": "code",
771
- "execution_count": null,
772
  "metadata": {},
773
  "outputs": [
774
  {
775
  "name": "stderr",
776
  "output_type": "stream",
777
  "text": [
778
- "C:\\Users\\f64\\AppData\\Local\\Temp\\ipykernel_36416\\1960408511.py:2: DeprecationWarning: DataFrameGroupBy.apply operated on the grouping columns. This behavior is deprecated, and in a future version of pandas the grouping columns will be excluded from the operation. Either pass `include_groups=False` to exclude the groupings or explicitly select the grouping columns after groupby to silence this warning.\n",
779
- " dgID.apply(lambda df: pd.Series(df[xyz].values[::-1].reshape(1,-1)[0])).reset_index().iloc[:,1:]\n"
780
  ]
781
  },
782
  {
@@ -800,6 +798,7 @@
800
  " <thead>\n",
801
  " <tr style=\"text-align: right;\">\n",
802
  " <th></th>\n",
 
803
  " <th>0</th>\n",
804
  " <th>1</th>\n",
805
  " <th>2</th>\n",
@@ -809,7 +808,6 @@
809
  " <th>6</th>\n",
810
  " <th>7</th>\n",
811
  " <th>8</th>\n",
812
- " <th>9</th>\n",
813
  " <th>...</th>\n",
814
  " <th>11</th>\n",
815
  " <th>12</th>\n",
@@ -826,6 +824,7 @@
826
  " <tbody>\n",
827
  " <tr>\n",
828
  " <th>0</th>\n",
 
829
  " <td>-200</td>\n",
830
  " <td>732</td>\n",
831
  " <td>257</td>\n",
@@ -835,7 +834,6 @@
835
  " <td>-22</td>\n",
836
  " <td>714</td>\n",
837
  " <td>277</td>\n",
838
- " <td>-202</td>\n",
839
  " <td>...</td>\n",
840
  " <td>382</td>\n",
841
  " <td>-221</td>\n",
@@ -850,6 +848,7 @@
850
  " </tr>\n",
851
  " <tr>\n",
852
  " <th>1</th>\n",
 
853
  " <td>202</td>\n",
854
  " <td>486</td>\n",
855
  " <td>-547</td>\n",
@@ -859,7 +858,6 @@
859
  " <td>-222</td>\n",
860
  " <td>525</td>\n",
861
  " <td>-178</td>\n",
862
- " <td>-102</td>\n",
863
  " <td>...</td>\n",
864
  " <td>22</td>\n",
865
  " <td>-2</td>\n",
@@ -874,6 +872,7 @@
874
  " </tr>\n",
875
  " <tr>\n",
876
  " <th>2</th>\n",
 
877
  " <td>-302</td>\n",
878
  " <td>336</td>\n",
879
  " <td>-443</td>\n",
@@ -883,7 +882,6 @@
883
  " <td>-201</td>\n",
884
  " <td>336</td>\n",
885
  " <td>-206</td>\n",
886
- " <td>121</td>\n",
887
  " <td>...</td>\n",
888
  " <td>-175</td>\n",
889
  " <td>-201</td>\n",
@@ -898,6 +896,7 @@
898
  " </tr>\n",
899
  " <tr>\n",
900
  " <th>3</th>\n",
 
901
  " <td>401</td>\n",
902
  " <td>681</td>\n",
903
  " <td>768</td>\n",
@@ -907,7 +906,6 @@
907
  " <td>220</td>\n",
908
  " <td>712</td>\n",
909
  " <td>694</td>\n",
910
- " <td>401</td>\n",
911
  " <td>...</td>\n",
912
  " <td>544</td>\n",
913
  " <td>-202</td>\n",
@@ -922,6 +920,7 @@
922
  " </tr>\n",
923
  " <tr>\n",
924
  " <th>4</th>\n",
 
925
  " <td>-222</td>\n",
926
  " <td>525</td>\n",
927
  " <td>-178</td>\n",
@@ -931,7 +930,6 @@
931
  " <td>-2</td>\n",
932
  " <td>557</td>\n",
933
  " <td>58</td>\n",
934
- " <td>200</td>\n",
935
  " <td>...</td>\n",
936
  " <td>50</td>\n",
937
  " <td>201</td>\n",
@@ -946,6 +944,7 @@
946
  " </tr>\n",
947
  " <tr>\n",
948
  " <th>5</th>\n",
 
949
  " <td>21</td>\n",
950
  " <td>405</td>\n",
951
  " <td>-173</td>\n",
@@ -955,7 +954,6 @@
955
  " <td>-200</td>\n",
956
  " <td>377</td>\n",
957
  " <td>-150</td>\n",
958
- " <td>-110</td>\n",
959
  " <td>...</td>\n",
960
  " <td>-91</td>\n",
961
  " <td>-12</td>\n",
@@ -970,6 +968,7 @@
970
  " </tr>\n",
971
  " <tr>\n",
972
  " <th>6</th>\n",
 
973
  " <td>-102</td>\n",
974
  " <td>616</td>\n",
975
  " <td>22</td>\n",
@@ -979,7 +978,6 @@
979
  " <td>200</td>\n",
980
  " <td>572</td>\n",
981
  " <td>50</td>\n",
982
- " <td>201</td>\n",
983
  " <td>...</td>\n",
984
  " <td>-36</td>\n",
985
  " <td>-202</td>\n",
@@ -994,6 +992,7 @@
994
  " </tr>\n",
995
  " <tr>\n",
996
  " <th>7</th>\n",
 
997
  " <td>-302</td>\n",
998
  " <td>279</td>\n",
999
  " <td>-2298</td>\n",
@@ -1003,7 +1002,6 @@
1003
  " <td>-220</td>\n",
1004
  " <td>409</td>\n",
1005
  " <td>-362</td>\n",
1006
- " <td>-12</td>\n",
1007
  " <td>...</td>\n",
1008
  " <td>-393</td>\n",
1009
  " <td>512</td>\n",
@@ -1018,6 +1016,7 @@
1018
  " </tr>\n",
1019
  " <tr>\n",
1020
  " <th>8</th>\n",
 
1021
  " <td>-114</td>\n",
1022
  " <td>277</td>\n",
1023
  " <td>-97</td>\n",
@@ -1027,7 +1026,6 @@
1027
  " <td>-220</td>\n",
1028
  " <td>284</td>\n",
1029
  " <td>-602</td>\n",
1030
- " <td>-122</td>\n",
1031
  " <td>...</td>\n",
1032
  " <td>-860</td>\n",
1033
  " <td>222</td>\n",
@@ -1042,6 +1040,7 @@
1042
  " </tr>\n",
1043
  " <tr>\n",
1044
  " <th>9</th>\n",
 
1045
  " <td>-210</td>\n",
1046
  " <td>529</td>\n",
1047
  " <td>-943</td>\n",
@@ -1051,7 +1050,6 @@
1051
  " <td>-221</td>\n",
1052
  " <td>577</td>\n",
1053
  " <td>-859</td>\n",
1054
- " <td>-211</td>\n",
1055
  " <td>...</td>\n",
1056
  " <td>-752</td>\n",
1057
  " <td>-122</td>\n",
@@ -1066,6 +1064,7 @@
1066
  " </tr>\n",
1067
  " <tr>\n",
1068
  " <th>10</th>\n",
 
1069
  " <td>-200</td>\n",
1070
  " <td>320</td>\n",
1071
  " <td>82</td>\n",
@@ -1075,7 +1074,6 @@
1075
  " <td>22</td>\n",
1076
  " <td>336</td>\n",
1077
  " <td>-26</td>\n",
1078
- " <td>122</td>\n",
1079
  " <td>...</td>\n",
1080
  " <td>-106</td>\n",
1081
  " <td>-302</td>\n",
@@ -1090,6 +1088,7 @@
1090
  " </tr>\n",
1091
  " <tr>\n",
1092
  " <th>11</th>\n",
 
1093
  " <td>-201</td>\n",
1094
  " <td>612</td>\n",
1095
  " <td>63</td>\n",
@@ -1099,7 +1098,6 @@
1099
  " <td>-103</td>\n",
1100
  " <td>620</td>\n",
1101
  " <td>261</td>\n",
1102
- " <td>22</td>\n",
1103
  " <td>...</td>\n",
1104
  " <td>250</td>\n",
1105
  " <td>402</td>\n",
@@ -1114,6 +1112,7 @@
1114
  " </tr>\n",
1115
  " <tr>\n",
1116
  " <th>12</th>\n",
 
1117
  " <td>102</td>\n",
1118
  " <td>578</td>\n",
1119
  " <td>-830</td>\n",
@@ -1123,7 +1122,6 @@
1123
  " <td>-211</td>\n",
1124
  " <td>579</td>\n",
1125
  " <td>-752</td>\n",
1126
- " <td>-122</td>\n",
1127
  " <td>...</td>\n",
1128
  " <td>-592</td>\n",
1129
  " <td>-21</td>\n",
@@ -1138,6 +1136,7 @@
1138
  " </tr>\n",
1139
  " <tr>\n",
1140
  " <th>13</th>\n",
 
1141
  " <td>-2</td>\n",
1142
  " <td>550</td>\n",
1143
  " <td>736</td>\n",
@@ -1147,7 +1146,6 @@
1147
  " <td>-112</td>\n",
1148
  " <td>527</td>\n",
1149
  " <td>840</td>\n",
1150
- " <td>320</td>\n",
1151
  " <td>...</td>\n",
1152
  " <td>906</td>\n",
1153
  " <td>-221</td>\n",
@@ -1162,6 +1160,7 @@
1162
  " </tr>\n",
1163
  " <tr>\n",
1164
  " <th>14</th>\n",
 
1165
  " <td>-300</td>\n",
1166
  " <td>554</td>\n",
1167
  " <td>-130</td>\n",
@@ -1171,7 +1170,6 @@
1171
  " <td>221</td>\n",
1172
  " <td>581</td>\n",
1173
  " <td>-249</td>\n",
1174
- " <td>113</td>\n",
1175
  " <td>...</td>\n",
1176
  " <td>-242</td>\n",
1177
  " <td>-220</td>\n",
@@ -1186,6 +1184,7 @@
1186
  " </tr>\n",
1187
  " <tr>\n",
1188
  " <th>15</th>\n",
 
1189
  " <td>-322</td>\n",
1190
  " <td>381</td>\n",
1191
  " <td>-1133</td>\n",
@@ -1195,7 +1194,6 @@
1195
  " <td>223</td>\n",
1196
  " <td>370</td>\n",
1197
  " <td>-1289</td>\n",
1198
- " <td>-520</td>\n",
1199
  " <td>...</td>\n",
1200
  " <td>-1204</td>\n",
1201
  " <td>-320</td>\n",
@@ -1210,6 +1208,7 @@
1210
  " </tr>\n",
1211
  " <tr>\n",
1212
  " <th>16</th>\n",
 
1213
  " <td>-202</td>\n",
1214
  " <td>316</td>\n",
1215
  " <td>-1791</td>\n",
@@ -1219,7 +1218,6 @@
1219
  " <td>-22</td>\n",
1220
  " <td>421</td>\n",
1221
  " <td>-1718</td>\n",
1222
- " <td>-511</td>\n",
1223
  " <td>...</td>\n",
1224
  " <td>-1547</td>\n",
1225
  " <td>201</td>\n",
@@ -1234,6 +1232,7 @@
1234
  " </tr>\n",
1235
  " <tr>\n",
1236
  " <th>17</th>\n",
 
1237
  " <td>-203</td>\n",
1238
  " <td>438</td>\n",
1239
  " <td>-86</td>\n",
@@ -1243,7 +1242,6 @@
1243
  " <td>-422</td>\n",
1244
  " <td>453</td>\n",
1245
  " <td>745</td>\n",
1246
- " <td>-222</td>\n",
1247
  " <td>...</td>\n",
1248
  " <td>921</td>\n",
1249
  " <td>211</td>\n",
@@ -1258,6 +1256,7 @@
1258
  " </tr>\n",
1259
  " <tr>\n",
1260
  " <th>18</th>\n",
 
1261
  " <td>724</td>\n",
1262
  " <td>526</td>\n",
1263
  " <td>-5020</td>\n",
@@ -1267,7 +1266,6 @@
1267
  " <td>-532</td>\n",
1268
  " <td>352</td>\n",
1269
  " <td>-6875</td>\n",
1270
- " <td>-453</td>\n",
1271
  " <td>...</td>\n",
1272
  " <td>-6739</td>\n",
1273
  " <td>260</td>\n",
@@ -1282,6 +1280,7 @@
1282
  " </tr>\n",
1283
  " <tr>\n",
1284
  " <th>19</th>\n",
 
1285
  " <td>400</td>\n",
1286
  " <td>503</td>\n",
1287
  " <td>905</td>\n",
@@ -1291,7 +1290,6 @@
1291
  " <td>-121</td>\n",
1292
  " <td>489</td>\n",
1293
  " <td>299</td>\n",
1294
- " <td>320</td>\n",
1295
  " <td>...</td>\n",
1296
  " <td>283</td>\n",
1297
  " <td>-123</td>\n",
@@ -1306,85 +1304,117 @@
1306
  " </tr>\n",
1307
  " </tbody>\n",
1308
  "</table>\n",
1309
- "<p>20 rows × 21 columns</p>\n",
1310
  "</div>"
1311
  ],
1312
  "text/plain": [
1313
- " 0 1 2 3 4 5 6 7 8 9 ... 11 \\\n",
1314
- "0 -200 732 257 211 746 312 -22 714 277 -202 ... 382 \n",
1315
- "1 202 486 -547 -320 452 -505 -222 525 -178 -102 ... 22 \n",
1316
- "2 -302 336 -443 -202 343 -257 -201 336 -206 121 ... -175 \n",
1317
- "3 401 681 768 -212 705 660 220 712 694 401 ... 544 \n",
1318
- "4 -222 525 -178 -102 616 22 -2 557 58 200 ... 50 \n",
1319
- "5 21 405 -173 -111 427 -180 -200 377 -150 -110 ... -91 \n",
1320
- "6 -102 616 22 -2 557 58 200 572 50 201 ... -36 \n",
1321
- "7 -302 279 -2298 -502 282 -1456 -220 409 -362 -12 ... -393 \n",
1322
- "8 -114 277 -97 2 247 -329 -220 284 -602 -122 ... -860 \n",
1323
- "9 -210 529 -943 102 578 -830 -221 577 -859 -211 ... -752 \n",
1324
- "10 -200 320 82 121 289 58 22 336 -26 122 ... -106 \n",
1325
- "11 -201 612 63 -212 604 201 -103 620 261 22 ... 250 \n",
1326
- "12 102 578 -830 -221 577 -859 -211 579 -752 -122 ... -592 \n",
1327
- "13 -2 550 736 220 531 814 -112 527 840 320 ... 906 \n",
1328
- "14 -300 554 -130 222 598 -85 221 581 -249 113 ... -242 \n",
1329
- "15 -322 381 -1133 222 413 -1103 223 370 -1289 -520 ... -1204 \n",
1330
- "16 -202 316 -1791 -232 333 -1659 -22 421 -1718 -511 ... -1547 \n",
1331
- "17 -203 438 -86 -521 436 327 -422 453 745 -222 ... 921 \n",
1332
- "18 724 526 -5020 -412 345 -7138 -532 352 -6875 -453 ... -6739 \n",
1333
- "19 400 503 905 502 490 564 -121 489 299 320 ... 283 \n",
1334
  "\n",
1335
- " 12 13 14 15 16 17 18 19 20 \n",
1336
- "0 -221 703 505 200 711 556 111 702 536 \n",
1337
- "1 -2 557 58 200 572 50 201 584 -36 \n",
1338
- "2 -201 357 -235 21 392 -205 -222 412 -343 \n",
1339
- "3 -202 644 372 202 625 446 222 643 403 \n",
1340
- "4 201 584 -36 -202 585 -4 0 645 109 \n",
1341
- "5 -12 316 -98 -200 356 -136 211 335 -157 \n",
1342
- "6 -202 585 -4 0 645 109 0 600 157 \n",
1343
- "7 512 411 -487 -212 460 -595 -122 433 -670 \n",
1344
- "8 222 271 -1227 420 253 -1668 -212 303 -1919 \n",
1345
- "9 -122 636 -592 -21 602 -558 -200 573 -505 \n",
1346
- "10 -302 422 -158 -202 415 -143 12 416 -340 \n",
1347
- "11 402 616 161 -212 559 20 -210 547 161 \n",
1348
- "12 -21 602 -558 -200 573 -505 222 587 -400 \n",
1349
- "13 -221 562 1013 -231 563 1342 212 546 1557 \n",
1350
- "14 -220 561 -13 -102 601 258 -221 575 438 \n",
1351
- "15 -320 452 -732 -220 465 -473 11 425 -396 \n",
1352
- "16 201 481 -1213 -220 433 -1375 222 404 -1306 \n",
1353
- "17 211 483 813 401 492 535 220 436 318 \n",
1354
- "18 260 301 -6366 -623 318 -5477 -512 357 -3812 \n",
1355
- "19 -123 478 234 22 516 433 -220 487 741 \n",
1356
  "\n",
1357
- "[20 rows x 21 columns]"
1358
  ]
1359
  },
1360
- "execution_count": 31,
1361
  "metadata": {},
1362
  "output_type": "execute_result"
1363
  }
1364
  ],
1365
  "source": [
1366
- "#dgID.apply(lambda df: df[xyz].values.reshape(1,21)).reset_index()\n",
1367
- "dgID.apply(lambda df: pd.Series(df[xyz].values[::-1].reshape(1,-1)[0])).reset_index().iloc[:,1:]"
1368
  ]
1369
  },
1370
  {
1371
  "cell_type": "code",
1372
- "execution_count": null,
1373
  "metadata": {},
1374
  "outputs": [
1375
  {
1376
  "data": {
1377
  "text/plain": [
1378
- "'n:\\\\Makarov\\\\Development\\\\HuggingFaceSpacesGit\\\\streamlit\\\\static'"
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1379
  ]
1380
  },
1381
- "execution_count": 8,
1382
  "metadata": {},
1383
  "output_type": "execute_result"
1384
  }
1385
  ],
1386
  "source": [
1387
- "os.getcwd()"
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1388
  ]
1389
  }
1390
  ],
 
2
  "cells": [
3
  {
4
  "cell_type": "code",
5
+ "execution_count": 11,
6
  "metadata": {},
7
  "outputs": [],
8
  "source": [
9
  "#@title IMPORT\n",
10
+ "import io,os,re,sys,math,time,uuid,ctypes,pickle,psutil,random,shutil,string,urllib,decimal,datetime,itertools,traceback,collections,platform\n",
11
  "import matplotlib.pyplot as plt, seaborn as sns, plotly.express as px\n",
12
  "import numpy as np, pandas as pd\n",
13
  "\n",
 
16
  },
17
  {
18
  "cell_type": "code",
19
+ "execution_count": 12,
20
  "metadata": {},
21
  "outputs": [
22
  {
 
25
  "text": [
26
  "<>:1: SyntaxWarning: invalid escape sequence '\\M'\n",
27
  "<>:1: SyntaxWarning: invalid escape sequence '\\M'\n",
28
+ "C:\\Users\\f64\\AppData\\Local\\Temp\\ipykernel_34940\\1255343956.py:1: SyntaxWarning: invalid escape sequence '\\M'\n",
29
  " path1 = \"N:\\Makarov\\Development\\Python\\Jupiter Notebooks\\Gaziev CSV\\TestData_1504_AB_soloV_gaziev.zip\"\n"
30
  ]
31
  },
 
228
  "[12010 rows x 10 columns]"
229
  ]
230
  },
231
+ "execution_count": 12,
232
  "metadata": {},
233
  "output_type": "execute_result"
234
  }
 
249
  },
250
  {
251
  "cell_type": "code",
252
+ "execution_count": 13,
253
  "metadata": {},
254
  "outputs": [
255
  {
 
270
  },
271
  {
272
  "cell_type": "code",
273
+ "execution_count": 14,
274
  "metadata": {},
275
  "outputs": [
276
  {
 
437
  "18 AAA011113 21 392 -205"
438
  ]
439
  },
440
+ "execution_count": 14,
441
  "metadata": {},
442
  "output_type": "execute_result"
443
  }
 
456
  },
457
  {
458
  "cell_type": "code",
459
+ "execution_count": 15,
460
  "metadata": {},
461
  "outputs": [
462
  {
 
470
  "name": "stderr",
471
  "output_type": "stream",
472
  "text": [
473
+ "C:\\Users\\f64\\AppData\\Local\\Temp\\ipykernel_34940\\1846308829.py:2: DeprecationWarning: DataFrameGroupBy.apply operated on the grouping columns. This behavior is deprecated, and in a future version of pandas the grouping columns will be excluded from the operation. Either pass `include_groups=False` to exclude the groupings or explicitly select the grouping columns after groupby to silence this warning.\n",
474
  " print(f\"{set(dgID.apply(len))=}\")\n",
475
+ "C:\\Users\\f64\\AppData\\Local\\Temp\\ipykernel_34940\\1846308829.py:4: DeprecationWarning: DataFrameGroupBy.apply operated on the grouping columns. This behavior is deprecated, and in a future version of pandas the grouping columns will be excluded from the operation. Either pass `include_groups=False` to exclude the groupings or explicitly select the grouping columns after groupby to silence this warning.\n",
476
  " dgID.apply(len).reset_index()\n"
477
  ]
478
  },
 
630
  "19 DDD011113 7"
631
  ]
632
  },
633
+ "execution_count": 15,
634
  "metadata": {},
635
  "output_type": "execute_result"
636
  }
 
644
  },
645
  {
646
  "cell_type": "code",
647
+ "execution_count": 16,
648
  "metadata": {},
649
  "outputs": [
650
  {
651
  "name": "stdout",
652
  "output_type": "stream",
653
  "text": [
 
 
654
  "[['-300' '554' '-130' '222' '598' '-85' '221' '581' '-249' '113' '567'\n",
655
  " '-242' '-220' '561' '-13' '-102' '601' '258' '-221' '575' '438']]\n"
656
  ]
 
747
  "119 BBB011117 -300 554 -130"
748
  ]
749
  },
750
+ "execution_count": 16,
751
  "metadata": {},
752
  "output_type": "execute_result"
753
  }
 
766
  },
767
  {
768
  "cell_type": "code",
769
+ "execution_count": 17,
770
  "metadata": {},
771
  "outputs": [
772
  {
773
  "name": "stderr",
774
  "output_type": "stream",
775
  "text": [
776
+ "C:\\Users\\f64\\AppData\\Local\\Temp\\ipykernel_34940\\1487317556.py:1: DeprecationWarning: DataFrameGroupBy.apply operated on the grouping columns. This behavior is deprecated, and in a future version of pandas the grouping columns will be excluded from the operation. Either pass `include_groups=False` to exclude the groupings or explicitly select the grouping columns after groupby to silence this warning.\n",
777
+ " df_packs_reshaped = dgID.apply(lambda df: pd.Series(df[xyz].values[::-1].reshape(1,-1)[0])).reset_index() # правильный порядок\n"
778
  ]
779
  },
780
  {
 
798
  " <thead>\n",
799
  " <tr style=\"text-align: right;\">\n",
800
  " <th></th>\n",
801
+ " <th>ID</th>\n",
802
  " <th>0</th>\n",
803
  " <th>1</th>\n",
804
  " <th>2</th>\n",
 
808
  " <th>6</th>\n",
809
  " <th>7</th>\n",
810
  " <th>8</th>\n",
 
811
  " <th>...</th>\n",
812
  " <th>11</th>\n",
813
  " <th>12</th>\n",
 
824
  " <tbody>\n",
825
  " <tr>\n",
826
  " <th>0</th>\n",
827
+ " <td>AAA011111</td>\n",
828
  " <td>-200</td>\n",
829
  " <td>732</td>\n",
830
  " <td>257</td>\n",
 
834
  " <td>-22</td>\n",
835
  " <td>714</td>\n",
836
  " <td>277</td>\n",
 
837
  " <td>...</td>\n",
838
  " <td>382</td>\n",
839
  " <td>-221</td>\n",
 
848
  " </tr>\n",
849
  " <tr>\n",
850
  " <th>1</th>\n",
851
+ " <td>AAA011112</td>\n",
852
  " <td>202</td>\n",
853
  " <td>486</td>\n",
854
  " <td>-547</td>\n",
 
858
  " <td>-222</td>\n",
859
  " <td>525</td>\n",
860
  " <td>-178</td>\n",
 
861
  " <td>...</td>\n",
862
  " <td>22</td>\n",
863
  " <td>-2</td>\n",
 
872
  " </tr>\n",
873
  " <tr>\n",
874
  " <th>2</th>\n",
875
+ " <td>AAA011113</td>\n",
876
  " <td>-302</td>\n",
877
  " <td>336</td>\n",
878
  " <td>-443</td>\n",
 
882
  " <td>-201</td>\n",
883
  " <td>336</td>\n",
884
  " <td>-206</td>\n",
 
885
  " <td>...</td>\n",
886
  " <td>-175</td>\n",
887
  " <td>-201</td>\n",
 
896
  " </tr>\n",
897
  " <tr>\n",
898
  " <th>3</th>\n",
899
+ " <td>AAA011114</td>\n",
900
  " <td>401</td>\n",
901
  " <td>681</td>\n",
902
  " <td>768</td>\n",
 
906
  " <td>220</td>\n",
907
  " <td>712</td>\n",
908
  " <td>694</td>\n",
 
909
  " <td>...</td>\n",
910
  " <td>544</td>\n",
911
  " <td>-202</td>\n",
 
920
  " </tr>\n",
921
  " <tr>\n",
922
  " <th>4</th>\n",
923
+ " <td>AAA011115</td>\n",
924
  " <td>-222</td>\n",
925
  " <td>525</td>\n",
926
  " <td>-178</td>\n",
 
930
  " <td>-2</td>\n",
931
  " <td>557</td>\n",
932
  " <td>58</td>\n",
 
933
  " <td>...</td>\n",
934
  " <td>50</td>\n",
935
  " <td>201</td>\n",
 
944
  " </tr>\n",
945
  " <tr>\n",
946
  " <th>5</th>\n",
947
+ " <td>AAA011116</td>\n",
948
  " <td>21</td>\n",
949
  " <td>405</td>\n",
950
  " <td>-173</td>\n",
 
954
  " <td>-200</td>\n",
955
  " <td>377</td>\n",
956
  " <td>-150</td>\n",
 
957
  " <td>...</td>\n",
958
  " <td>-91</td>\n",
959
  " <td>-12</td>\n",
 
968
  " </tr>\n",
969
  " <tr>\n",
970
  " <th>6</th>\n",
971
+ " <td>AAA011117</td>\n",
972
  " <td>-102</td>\n",
973
  " <td>616</td>\n",
974
  " <td>22</td>\n",
 
978
  " <td>200</td>\n",
979
  " <td>572</td>\n",
980
  " <td>50</td>\n",
 
981
  " <td>...</td>\n",
982
  " <td>-36</td>\n",
983
  " <td>-202</td>\n",
 
992
  " </tr>\n",
993
  " <tr>\n",
994
  " <th>7</th>\n",
995
+ " <td>AAA011118</td>\n",
996
  " <td>-302</td>\n",
997
  " <td>279</td>\n",
998
  " <td>-2298</td>\n",
 
1002
  " <td>-220</td>\n",
1003
  " <td>409</td>\n",
1004
  " <td>-362</td>\n",
 
1005
  " <td>...</td>\n",
1006
  " <td>-393</td>\n",
1007
  " <td>512</td>\n",
 
1016
  " </tr>\n",
1017
  " <tr>\n",
1018
  " <th>8</th>\n",
1019
+ " <td>BBB011111</td>\n",
1020
  " <td>-114</td>\n",
1021
  " <td>277</td>\n",
1022
  " <td>-97</td>\n",
 
1026
  " <td>-220</td>\n",
1027
  " <td>284</td>\n",
1028
  " <td>-602</td>\n",
 
1029
  " <td>...</td>\n",
1030
  " <td>-860</td>\n",
1031
  " <td>222</td>\n",
 
1040
  " </tr>\n",
1041
  " <tr>\n",
1042
  " <th>9</th>\n",
1043
+ " <td>BBB011112</td>\n",
1044
  " <td>-210</td>\n",
1045
  " <td>529</td>\n",
1046
  " <td>-943</td>\n",
 
1050
  " <td>-221</td>\n",
1051
  " <td>577</td>\n",
1052
  " <td>-859</td>\n",
 
1053
  " <td>...</td>\n",
1054
  " <td>-752</td>\n",
1055
  " <td>-122</td>\n",
 
1064
  " </tr>\n",
1065
  " <tr>\n",
1066
  " <th>10</th>\n",
1067
+ " <td>BBB011113</td>\n",
1068
  " <td>-200</td>\n",
1069
  " <td>320</td>\n",
1070
  " <td>82</td>\n",
 
1074
  " <td>22</td>\n",
1075
  " <td>336</td>\n",
1076
  " <td>-26</td>\n",
 
1077
  " <td>...</td>\n",
1078
  " <td>-106</td>\n",
1079
  " <td>-302</td>\n",
 
1088
  " </tr>\n",
1089
  " <tr>\n",
1090
  " <th>11</th>\n",
1091
+ " <td>BBB011114</td>\n",
1092
  " <td>-201</td>\n",
1093
  " <td>612</td>\n",
1094
  " <td>63</td>\n",
 
1098
  " <td>-103</td>\n",
1099
  " <td>620</td>\n",
1100
  " <td>261</td>\n",
 
1101
  " <td>...</td>\n",
1102
  " <td>250</td>\n",
1103
  " <td>402</td>\n",
 
1112
  " </tr>\n",
1113
  " <tr>\n",
1114
  " <th>12</th>\n",
1115
+ " <td>BBB011115</td>\n",
1116
  " <td>102</td>\n",
1117
  " <td>578</td>\n",
1118
  " <td>-830</td>\n",
 
1122
  " <td>-211</td>\n",
1123
  " <td>579</td>\n",
1124
  " <td>-752</td>\n",
 
1125
  " <td>...</td>\n",
1126
  " <td>-592</td>\n",
1127
  " <td>-21</td>\n",
 
1136
  " </tr>\n",
1137
  " <tr>\n",
1138
  " <th>13</th>\n",
1139
+ " <td>BBB011116</td>\n",
1140
  " <td>-2</td>\n",
1141
  " <td>550</td>\n",
1142
  " <td>736</td>\n",
 
1146
  " <td>-112</td>\n",
1147
  " <td>527</td>\n",
1148
  " <td>840</td>\n",
 
1149
  " <td>...</td>\n",
1150
  " <td>906</td>\n",
1151
  " <td>-221</td>\n",
 
1160
  " </tr>\n",
1161
  " <tr>\n",
1162
  " <th>14</th>\n",
1163
+ " <td>BBB011117</td>\n",
1164
  " <td>-300</td>\n",
1165
  " <td>554</td>\n",
1166
  " <td>-130</td>\n",
 
1170
  " <td>221</td>\n",
1171
  " <td>581</td>\n",
1172
  " <td>-249</td>\n",
 
1173
  " <td>...</td>\n",
1174
  " <td>-242</td>\n",
1175
  " <td>-220</td>\n",
 
1184
  " </tr>\n",
1185
  " <tr>\n",
1186
  " <th>15</th>\n",
1187
+ " <td>CCC011111</td>\n",
1188
  " <td>-322</td>\n",
1189
  " <td>381</td>\n",
1190
  " <td>-1133</td>\n",
 
1194
  " <td>223</td>\n",
1195
  " <td>370</td>\n",
1196
  " <td>-1289</td>\n",
 
1197
  " <td>...</td>\n",
1198
  " <td>-1204</td>\n",
1199
  " <td>-320</td>\n",
 
1208
  " </tr>\n",
1209
  " <tr>\n",
1210
  " <th>16</th>\n",
1211
+ " <td>CCC011112</td>\n",
1212
  " <td>-202</td>\n",
1213
  " <td>316</td>\n",
1214
  " <td>-1791</td>\n",
 
1218
  " <td>-22</td>\n",
1219
  " <td>421</td>\n",
1220
  " <td>-1718</td>\n",
 
1221
  " <td>...</td>\n",
1222
  " <td>-1547</td>\n",
1223
  " <td>201</td>\n",
 
1232
  " </tr>\n",
1233
  " <tr>\n",
1234
  " <th>17</th>\n",
1235
+ " <td>DDD011111</td>\n",
1236
  " <td>-203</td>\n",
1237
  " <td>438</td>\n",
1238
  " <td>-86</td>\n",
 
1242
  " <td>-422</td>\n",
1243
  " <td>453</td>\n",
1244
  " <td>745</td>\n",
 
1245
  " <td>...</td>\n",
1246
  " <td>921</td>\n",
1247
  " <td>211</td>\n",
 
1256
  " </tr>\n",
1257
  " <tr>\n",
1258
  " <th>18</th>\n",
1259
+ " <td>DDD011112</td>\n",
1260
  " <td>724</td>\n",
1261
  " <td>526</td>\n",
1262
  " <td>-5020</td>\n",
 
1266
  " <td>-532</td>\n",
1267
  " <td>352</td>\n",
1268
  " <td>-6875</td>\n",
 
1269
  " <td>...</td>\n",
1270
  " <td>-6739</td>\n",
1271
  " <td>260</td>\n",
 
1280
  " </tr>\n",
1281
  " <tr>\n",
1282
  " <th>19</th>\n",
1283
+ " <td>DDD011113</td>\n",
1284
  " <td>400</td>\n",
1285
  " <td>503</td>\n",
1286
  " <td>905</td>\n",
 
1290
  " <td>-121</td>\n",
1291
  " <td>489</td>\n",
1292
  " <td>299</td>\n",
 
1293
  " <td>...</td>\n",
1294
  " <td>283</td>\n",
1295
  " <td>-123</td>\n",
 
1304
  " </tr>\n",
1305
  " </tbody>\n",
1306
  "</table>\n",
1307
+ "<p>20 rows × 22 columns</p>\n",
1308
  "</div>"
1309
  ],
1310
  "text/plain": [
1311
+ " ID 0 1 2 3 4 5 6 7 8 ... \\\n",
1312
+ "0 AAA011111 -200 732 257 211 746 312 -22 714 277 ... \n",
1313
+ "1 AAA011112 202 486 -547 -320 452 -505 -222 525 -178 ... \n",
1314
+ "2 AAA011113 -302 336 -443 -202 343 -257 -201 336 -206 ... \n",
1315
+ "3 AAA011114 401 681 768 -212 705 660 220 712 694 ... \n",
1316
+ "4 AAA011115 -222 525 -178 -102 616 22 -2 557 58 ... \n",
1317
+ "5 AAA011116 21 405 -173 -111 427 -180 -200 377 -150 ... \n",
1318
+ "6 AAA011117 -102 616 22 -2 557 58 200 572 50 ... \n",
1319
+ "7 AAA011118 -302 279 -2298 -502 282 -1456 -220 409 -362 ... \n",
1320
+ "8 BBB011111 -114 277 -97 2 247 -329 -220 284 -602 ... \n",
1321
+ "9 BBB011112 -210 529 -943 102 578 -830 -221 577 -859 ... \n",
1322
+ "10 BBB011113 -200 320 82 121 289 58 22 336 -26 ... \n",
1323
+ "11 BBB011114 -201 612 63 -212 604 201 -103 620 261 ... \n",
1324
+ "12 BBB011115 102 578 -830 -221 577 -859 -211 579 -752 ... \n",
1325
+ "13 BBB011116 -2 550 736 220 531 814 -112 527 840 ... \n",
1326
+ "14 BBB011117 -300 554 -130 222 598 -85 221 581 -249 ... \n",
1327
+ "15 CCC011111 -322 381 -1133 222 413 -1103 223 370 -1289 ... \n",
1328
+ "16 CCC011112 -202 316 -1791 -232 333 -1659 -22 421 -1718 ... \n",
1329
+ "17 DDD011111 -203 438 -86 -521 436 327 -422 453 745 ... \n",
1330
+ "18 DDD011112 724 526 -5020 -412 345 -7138 -532 352 -6875 ... \n",
1331
+ "19 DDD011113 400 503 905 502 490 564 -121 489 299 ... \n",
1332
  "\n",
1333
+ " 11 12 13 14 15 16 17 18 19 20 \n",
1334
+ "0 382 -221 703 505 200 711 556 111 702 536 \n",
1335
+ "1 22 -2 557 58 200 572 50 201 584 -36 \n",
1336
+ "2 -175 -201 357 -235 21 392 -205 -222 412 -343 \n",
1337
+ "3 544 -202 644 372 202 625 446 222 643 403 \n",
1338
+ "4 50 201 584 -36 -202 585 -4 0 645 109 \n",
1339
+ "5 -91 -12 316 -98 -200 356 -136 211 335 -157 \n",
1340
+ "6 -36 -202 585 -4 0 645 109 0 600 157 \n",
1341
+ "7 -393 512 411 -487 -212 460 -595 -122 433 -670 \n",
1342
+ "8 -860 222 271 -1227 420 253 -1668 -212 303 -1919 \n",
1343
+ "9 -752 -122 636 -592 -21 602 -558 -200 573 -505 \n",
1344
+ "10 -106 -302 422 -158 -202 415 -143 12 416 -340 \n",
1345
+ "11 250 402 616 161 -212 559 20 -210 547 161 \n",
1346
+ "12 -592 -21 602 -558 -200 573 -505 222 587 -400 \n",
1347
+ "13 906 -221 562 1013 -231 563 1342 212 546 1557 \n",
1348
+ "14 -242 -220 561 -13 -102 601 258 -221 575 438 \n",
1349
+ "15 -1204 -320 452 -732 -220 465 -473 11 425 -396 \n",
1350
+ "16 -1547 201 481 -1213 -220 433 -1375 222 404 -1306 \n",
1351
+ "17 921 211 483 813 401 492 535 220 436 318 \n",
1352
+ "18 -6739 260 301 -6366 -623 318 -5477 -512 357 -3812 \n",
1353
+ "19 283 -123 478 234 22 516 433 -220 487 741 \n",
1354
  "\n",
1355
+ "[20 rows x 22 columns]"
1356
  ]
1357
  },
1358
+ "execution_count": 17,
1359
  "metadata": {},
1360
  "output_type": "execute_result"
1361
  }
1362
  ],
1363
  "source": [
1364
+ "df_packs_reshaped = dgID.apply(lambda df: pd.Series(df[xyz].values[::-1].reshape(1,-1)[0])).reset_index() # правильный порядок\n",
1365
+ "df_packs_reshaped #.iloc[:,1:]"
1366
  ]
1367
  },
1368
  {
1369
  "cell_type": "code",
1370
+ "execution_count": 18,
1371
  "metadata": {},
1372
  "outputs": [
1373
  {
1374
  "data": {
1375
  "text/plain": [
1376
+ "{'os.getcwd': 'n:\\\\Makarov\\\\Development\\\\HuggingFaceSpacesGit\\\\streamlit\\\\static',\n",
1377
+ " 'cpu_count': 6,\n",
1378
+ " 'os.listdir': ['test.ipynb', 'text.txt'],\n",
1379
+ " 'platform': 'Windows-10-10.0.19044-SP0',\n",
1380
+ " 'release': '10',\n",
1381
+ " 'node': 'f64-w10',\n",
1382
+ " 'processor': 'Intel64 Family 6 Model 158 Stepping 10, GenuineIntel',\n",
1383
+ " 'machine': 'AMD64',\n",
1384
+ " 'system': 'Windows',\n",
1385
+ " 'version': '10.0.19044',\n",
1386
+ " 'python_version': '3.12.4',\n",
1387
+ " 'python_implementation': 'CPython',\n",
1388
+ " 'uname': uname_result(system='Windows', node='f64-w10', release='10', version='10.0.19044', machine='AMD64'),\n",
1389
+ " 'libc_ver': ('', ''),\n",
1390
+ " 'architecture': ('64bit', 'WindowsPE')}"
1391
  ]
1392
  },
1393
+ "execution_count": 18,
1394
  "metadata": {},
1395
  "output_type": "execute_result"
1396
  }
1397
  ],
1398
  "source": [
1399
+ "dirParams = {\n",
1400
+ " \"os.getcwd\": os.getcwd(),\n",
1401
+ " \"cpu_count\": os.cpu_count(),\n",
1402
+ " #\"environ\": os.environ,\n",
1403
+ " \"os.listdir\": os.listdir(),\n",
1404
+ " \"platform\": platform.platform(),\n",
1405
+ " \"release\": platform.release(),\n",
1406
+ " \"node\": platform.node(),\n",
1407
+ " \"processor\": platform.processor(),\n",
1408
+ " \"machine\": platform.machine(),\n",
1409
+ " \"system\": platform.system(),\n",
1410
+ " \"version\": platform.version(),\n",
1411
+ " \"python_version\": platform.python_version(),\n",
1412
+ " \"python_implementation\": platform.python_implementation(),\n",
1413
+ " \"uname\": platform.uname(),\n",
1414
+ " \"libc_ver\": platform.libc_ver(),\n",
1415
+ " \"architecture\": platform.architecture(),\n",
1416
+ "}\n",
1417
+ "dirParams"
1418
  ]
1419
  }
1420
  ],