added wine attribute to csv
Browse files- .gitattributes +1 -0
- code/notebook.ipynb +288 -6
- data/csv/images_reviews_attributes.csv +3 -0
.gitattributes
CHANGED
@@ -1,3 +1,4 @@
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1 |
*.jsonl filter=lfs diff=lfs merge=lfs -text
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*.7z filter=lfs diff=lfs merge=lfs -text
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*.arrow filter=lfs diff=lfs merge=lfs -text
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+
*.csv filter=lfs diff=lfs merge=lfs -text
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2 |
*.jsonl filter=lfs diff=lfs merge=lfs -text
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3 |
*.7z filter=lfs diff=lfs merge=lfs -text
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4 |
*.arrow filter=lfs diff=lfs merge=lfs -text
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code/notebook.ipynb
CHANGED
@@ -2,7 +2,7 @@
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"cells": [
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{
|
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"cell_type": "code",
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-
"execution_count":
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"metadata": {},
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"outputs": [],
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"source": [
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@@ -11,7 +11,7 @@
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},
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{
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"cell_type": "code",
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-
"execution_count":
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"metadata": {},
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"outputs": [],
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"source": [
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@@ -65,7 +65,7 @@
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},
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{
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"cell_type": "code",
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-
"execution_count":
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"metadata": {},
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"outputs": [],
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"source": [
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@@ -99,8 +99,8 @@
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"write_jsonl(df_vintages, '../data/vintages/vintages_dataset.jsonl')\n",
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"\n",
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"# LOAD IMAGES 'small'\n",
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102 |
-
"df_small = df_image_review_attributes.sample(frac = 0.1)\n",
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103 |
-
"write_jsonl(df_small, '../data/small/small_dataset.jsonl')\n",
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104 |
"# df_napping\n",
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"# df_participant\n",
|
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"\n",
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@@ -857,16 +857,298 @@
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},
|
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{
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"cell_type": "code",
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-
"execution_count":
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"metadata": {},
|
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"outputs": [],
|
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"source": [
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|
864 |
"# read the json file\n",
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865 |
"with open('/Users/alka/Devel/GIT_LFS_SKIP_SMUDGE=1/metadata/all/all_dataset.jsonl') as json_file:\n",
|
866 |
" data = json_file.readlines()\n",
|
867 |
" data = [json.loads(line) for line in data] # convert string to dict format"
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]
|
869 |
},
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870 |
{
|
871 |
"cell_type": "code",
|
872 |
"execution_count": null,
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2 |
"cells": [
|
3 |
{
|
4 |
"cell_type": "code",
|
5 |
+
"execution_count": 1,
|
6 |
"metadata": {},
|
7 |
"outputs": [],
|
8 |
"source": [
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|
11 |
},
|
12 |
{
|
13 |
"cell_type": "code",
|
14 |
+
"execution_count": 2,
|
15 |
"metadata": {},
|
16 |
"outputs": [],
|
17 |
"source": [
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|
65 |
},
|
66 |
{
|
67 |
"cell_type": "code",
|
68 |
+
"execution_count": 5,
|
69 |
"metadata": {},
|
70 |
"outputs": [],
|
71 |
"source": [
|
|
|
99 |
"write_jsonl(df_vintages, '../data/vintages/vintages_dataset.jsonl')\n",
|
100 |
"\n",
|
101 |
"# LOAD IMAGES 'small'\n",
|
102 |
+
"# df_small = df_image_review_attributes.sample(frac = 0.1)\n",
|
103 |
+
"# write_jsonl(df_small, '../data/small/small_dataset.jsonl')\n",
|
104 |
"# df_napping\n",
|
105 |
"# df_participant\n",
|
106 |
"\n",
|
|
|
857 |
},
|
858 |
{
|
859 |
"cell_type": "code",
|
860 |
+
"execution_count": 3,
|
861 |
"metadata": {},
|
862 |
"outputs": [],
|
863 |
"source": [
|
864 |
+
"import json\n",
|
865 |
"# read the json file\n",
|
866 |
"with open('/Users/alka/Devel/GIT_LFS_SKIP_SMUDGE=1/metadata/all/all_dataset.jsonl') as json_file:\n",
|
867 |
" data = json_file.readlines()\n",
|
868 |
" data = [json.loads(line) for line in data] # convert string to dict format"
|
869 |
]
|
870 |
},
|
871 |
+
{
|
872 |
+
"cell_type": "code",
|
873 |
+
"execution_count": 5,
|
874 |
+
"metadata": {},
|
875 |
+
"outputs": [],
|
876 |
+
"source": [
|
877 |
+
"import pandas as pd\n",
|
878 |
+
"data_df = pd.DataFrame(data)"
|
879 |
+
]
|
880 |
+
},
|
881 |
+
{
|
882 |
+
"cell_type": "code",
|
883 |
+
"execution_count": 10,
|
884 |
+
"metadata": {},
|
885 |
+
"outputs": [],
|
886 |
+
"source": [
|
887 |
+
"aa = data_df.copy()"
|
888 |
+
]
|
889 |
+
},
|
890 |
+
{
|
891 |
+
"cell_type": "code",
|
892 |
+
"execution_count": 11,
|
893 |
+
"metadata": {},
|
894 |
+
"outputs": [],
|
895 |
+
"source": [
|
896 |
+
"# remove charactr p from the image column\n",
|
897 |
+
"aa['image'] = pd.DataFrame([item.replace('p/', '') for item in data_df.image if item is not None])"
|
898 |
+
]
|
899 |
+
},
|
900 |
+
{
|
901 |
+
"cell_type": "code",
|
902 |
+
"execution_count": 13,
|
903 |
+
"metadata": {},
|
904 |
+
"outputs": [
|
905 |
+
{
|
906 |
+
"data": {
|
907 |
+
"text/html": [
|
908 |
+
"<div>\n",
|
909 |
+
"<style scoped>\n",
|
910 |
+
" .dataframe tbody tr th:only-of-type {\n",
|
911 |
+
" vertical-align: middle;\n",
|
912 |
+
" }\n",
|
913 |
+
"\n",
|
914 |
+
" .dataframe tbody tr th {\n",
|
915 |
+
" vertical-align: top;\n",
|
916 |
+
" }\n",
|
917 |
+
"\n",
|
918 |
+
" .dataframe thead th {\n",
|
919 |
+
" text-align: right;\n",
|
920 |
+
" }\n",
|
921 |
+
"</style>\n",
|
922 |
+
"<table border=\"1\" class=\"dataframe\">\n",
|
923 |
+
" <thead>\n",
|
924 |
+
" <tr style=\"text-align: right;\">\n",
|
925 |
+
" <th></th>\n",
|
926 |
+
" <th>vintage_id</th>\n",
|
927 |
+
" <th>image</th>\n",
|
928 |
+
" <th>review</th>\n",
|
929 |
+
" <th>experiment_id</th>\n",
|
930 |
+
" <th>year</th>\n",
|
931 |
+
" <th>winery_id</th>\n",
|
932 |
+
" <th>wine_alcohol</th>\n",
|
933 |
+
" <th>country</th>\n",
|
934 |
+
" <th>region</th>\n",
|
935 |
+
" <th>price</th>\n",
|
936 |
+
" <th>rating</th>\n",
|
937 |
+
" <th>grape</th>\n",
|
938 |
+
" </tr>\n",
|
939 |
+
" </thead>\n",
|
940 |
+
" <tbody>\n",
|
941 |
+
" <tr>\n",
|
942 |
+
" <th>0</th>\n",
|
943 |
+
" <td>150301706</td>\n",
|
944 |
+
" <td>p/iVoa6qR6TSKjLeb1RoHWtQ.jpg</td>\n",
|
945 |
+
" <td>Ничего особого в нем не нашел. В меру сухое, в...</td>\n",
|
946 |
+
" <td>NaN</td>\n",
|
947 |
+
" <td>NaN</td>\n",
|
948 |
+
" <td>NaN</td>\n",
|
949 |
+
" <td>NaN</td>\n",
|
950 |
+
" <td>None</td>\n",
|
951 |
+
" <td>None</td>\n",
|
952 |
+
" <td>NaN</td>\n",
|
953 |
+
" <td>NaN</td>\n",
|
954 |
+
" <td>None</td>\n",
|
955 |
+
" </tr>\n",
|
956 |
+
" <tr>\n",
|
957 |
+
" <th>1</th>\n",
|
958 |
+
" <td>159555436</td>\n",
|
959 |
+
" <td>p/e2W_085qRbCQbZJVp_tzHA.jpg</td>\n",
|
960 |
+
" <td>None</td>\n",
|
961 |
+
" <td>NaN</td>\n",
|
962 |
+
" <td>NaN</td>\n",
|
963 |
+
" <td>NaN</td>\n",
|
964 |
+
" <td>NaN</td>\n",
|
965 |
+
" <td>None</td>\n",
|
966 |
+
" <td>None</td>\n",
|
967 |
+
" <td>NaN</td>\n",
|
968 |
+
" <td>NaN</td>\n",
|
969 |
+
" <td>None</td>\n",
|
970 |
+
" </tr>\n",
|
971 |
+
" <tr>\n",
|
972 |
+
" <th>2</th>\n",
|
973 |
+
" <td>146958680</td>\n",
|
974 |
+
" <td>p/DdLNo35SRiCMxpoKTiEXyQ.jpg</td>\n",
|
975 |
+
" <td>None</td>\n",
|
976 |
+
" <td>NaN</td>\n",
|
977 |
+
" <td>NaN</td>\n",
|
978 |
+
" <td>NaN</td>\n",
|
979 |
+
" <td>NaN</td>\n",
|
980 |
+
" <td>None</td>\n",
|
981 |
+
" <td>None</td>\n",
|
982 |
+
" <td>NaN</td>\n",
|
983 |
+
" <td>NaN</td>\n",
|
984 |
+
" <td>None</td>\n",
|
985 |
+
" </tr>\n",
|
986 |
+
" <tr>\n",
|
987 |
+
" <th>3</th>\n",
|
988 |
+
" <td>2014691</td>\n",
|
989 |
+
" <td>p/vi-1ygw7RXCM6Pnwx9C6CA.jpg</td>\n",
|
990 |
+
" <td>3,3/5. Белая Риоха. Бленд на основе виуры (75%...</td>\n",
|
991 |
+
" <td>NaN</td>\n",
|
992 |
+
" <td>NaN</td>\n",
|
993 |
+
" <td>NaN</td>\n",
|
994 |
+
" <td>NaN</td>\n",
|
995 |
+
" <td>None</td>\n",
|
996 |
+
" <td>None</td>\n",
|
997 |
+
" <td>NaN</td>\n",
|
998 |
+
" <td>NaN</td>\n",
|
999 |
+
" <td>None</td>\n",
|
1000 |
+
" </tr>\n",
|
1001 |
+
" <tr>\n",
|
1002 |
+
" <th>4</th>\n",
|
1003 |
+
" <td>153305559</td>\n",
|
1004 |
+
" <td>p/1pjborIfR1Wdlr35jEHbtA.jpg</td>\n",
|
1005 |
+
" <td>Parfum! Super frumos!</td>\n",
|
1006 |
+
" <td>NaN</td>\n",
|
1007 |
+
" <td>NaN</td>\n",
|
1008 |
+
" <td>NaN</td>\n",
|
1009 |
+
" <td>NaN</td>\n",
|
1010 |
+
" <td>None</td>\n",
|
1011 |
+
" <td>None</td>\n",
|
1012 |
+
" <td>NaN</td>\n",
|
1013 |
+
" <td>NaN</td>\n",
|
1014 |
+
" <td>None</td>\n",
|
1015 |
+
" </tr>\n",
|
1016 |
+
" <tr>\n",
|
1017 |
+
" <th>5</th>\n",
|
1018 |
+
" <td>162913950</td>\n",
|
1019 |
+
" <td>p/kDz5LBlFRz2wb61xaMj_Dw.jpg</td>\n",
|
1020 |
+
" <td>Bom vinho</td>\n",
|
1021 |
+
" <td>NaN</td>\n",
|
1022 |
+
" <td>NaN</td>\n",
|
1023 |
+
" <td>NaN</td>\n",
|
1024 |
+
" <td>NaN</td>\n",
|
1025 |
+
" <td>None</td>\n",
|
1026 |
+
" <td>None</td>\n",
|
1027 |
+
" <td>NaN</td>\n",
|
1028 |
+
" <td>NaN</td>\n",
|
1029 |
+
" <td>None</td>\n",
|
1030 |
+
" </tr>\n",
|
1031 |
+
" <tr>\n",
|
1032 |
+
" <th>6</th>\n",
|
1033 |
+
" <td>14230455</td>\n",
|
1034 |
+
" <td>p/EJQLq-qLShSP-uf2Tg-G1g.jpg</td>\n",
|
1035 |
+
" <td>None</td>\n",
|
1036 |
+
" <td>NaN</td>\n",
|
1037 |
+
" <td>NaN</td>\n",
|
1038 |
+
" <td>NaN</td>\n",
|
1039 |
+
" <td>NaN</td>\n",
|
1040 |
+
" <td>None</td>\n",
|
1041 |
+
" <td>None</td>\n",
|
1042 |
+
" <td>NaN</td>\n",
|
1043 |
+
" <td>NaN</td>\n",
|
1044 |
+
" <td>None</td>\n",
|
1045 |
+
" </tr>\n",
|
1046 |
+
" <tr>\n",
|
1047 |
+
" <th>7</th>\n",
|
1048 |
+
" <td>159888939</td>\n",
|
1049 |
+
" <td>p/MhhKQteWSXW0gYUNnvHs6A.jpg</td>\n",
|
1050 |
+
" <td>V nice whitr</td>\n",
|
1051 |
+
" <td>NaN</td>\n",
|
1052 |
+
" <td>NaN</td>\n",
|
1053 |
+
" <td>NaN</td>\n",
|
1054 |
+
" <td>NaN</td>\n",
|
1055 |
+
" <td>None</td>\n",
|
1056 |
+
" <td>None</td>\n",
|
1057 |
+
" <td>NaN</td>\n",
|
1058 |
+
" <td>NaN</td>\n",
|
1059 |
+
" <td>None</td>\n",
|
1060 |
+
" </tr>\n",
|
1061 |
+
" <tr>\n",
|
1062 |
+
" <th>8</th>\n",
|
1063 |
+
" <td>3261951</td>\n",
|
1064 |
+
" <td>p/fdsdbl6XR2ynvoQnNYLXQQ.jpg</td>\n",
|
1065 |
+
" <td>Great label and ok tasting. Not the best but n...</td>\n",
|
1066 |
+
" <td>NaN</td>\n",
|
1067 |
+
" <td>NaN</td>\n",
|
1068 |
+
" <td>NaN</td>\n",
|
1069 |
+
" <td>NaN</td>\n",
|
1070 |
+
" <td>None</td>\n",
|
1071 |
+
" <td>None</td>\n",
|
1072 |
+
" <td>NaN</td>\n",
|
1073 |
+
" <td>NaN</td>\n",
|
1074 |
+
" <td>None</td>\n",
|
1075 |
+
" </tr>\n",
|
1076 |
+
" <tr>\n",
|
1077 |
+
" <th>9</th>\n",
|
1078 |
+
" <td>32363311</td>\n",
|
1079 |
+
" <td>p/BQkoD9sXQi-EIk3e2cG-YA.jpg</td>\n",
|
1080 |
+
" <td>None</td>\n",
|
1081 |
+
" <td>NaN</td>\n",
|
1082 |
+
" <td>NaN</td>\n",
|
1083 |
+
" <td>NaN</td>\n",
|
1084 |
+
" <td>NaN</td>\n",
|
1085 |
+
" <td>None</td>\n",
|
1086 |
+
" <td>None</td>\n",
|
1087 |
+
" <td>NaN</td>\n",
|
1088 |
+
" <td>NaN</td>\n",
|
1089 |
+
" <td>None</td>\n",
|
1090 |
+
" </tr>\n",
|
1091 |
+
" </tbody>\n",
|
1092 |
+
"</table>\n",
|
1093 |
+
"</div>"
|
1094 |
+
],
|
1095 |
+
"text/plain": [
|
1096 |
+
" vintage_id image \\\n",
|
1097 |
+
"0 150301706 p/iVoa6qR6TSKjLeb1RoHWtQ.jpg \n",
|
1098 |
+
"1 159555436 p/e2W_085qRbCQbZJVp_tzHA.jpg \n",
|
1099 |
+
"2 146958680 p/DdLNo35SRiCMxpoKTiEXyQ.jpg \n",
|
1100 |
+
"3 2014691 p/vi-1ygw7RXCM6Pnwx9C6CA.jpg \n",
|
1101 |
+
"4 153305559 p/1pjborIfR1Wdlr35jEHbtA.jpg \n",
|
1102 |
+
"5 162913950 p/kDz5LBlFRz2wb61xaMj_Dw.jpg \n",
|
1103 |
+
"6 14230455 p/EJQLq-qLShSP-uf2Tg-G1g.jpg \n",
|
1104 |
+
"7 159888939 p/MhhKQteWSXW0gYUNnvHs6A.jpg \n",
|
1105 |
+
"8 3261951 p/fdsdbl6XR2ynvoQnNYLXQQ.jpg \n",
|
1106 |
+
"9 32363311 p/BQkoD9sXQi-EIk3e2cG-YA.jpg \n",
|
1107 |
+
"\n",
|
1108 |
+
" review experiment_id year \\\n",
|
1109 |
+
"0 Ничего особого в нем не нашел. В меру сухое, в... NaN NaN \n",
|
1110 |
+
"1 None NaN NaN \n",
|
1111 |
+
"2 None NaN NaN \n",
|
1112 |
+
"3 3,3/5. Белая Риоха. Бленд на основе виуры (75%... NaN NaN \n",
|
1113 |
+
"4 Parfum! Super frumos! NaN NaN \n",
|
1114 |
+
"5 Bom vinho NaN NaN \n",
|
1115 |
+
"6 None NaN NaN \n",
|
1116 |
+
"7 V nice whitr NaN NaN \n",
|
1117 |
+
"8 Great label and ok tasting. Not the best but n... NaN NaN \n",
|
1118 |
+
"9 None NaN NaN \n",
|
1119 |
+
"\n",
|
1120 |
+
" winery_id wine_alcohol country region price rating grape \n",
|
1121 |
+
"0 NaN NaN None None NaN NaN None \n",
|
1122 |
+
"1 NaN NaN None None NaN NaN None \n",
|
1123 |
+
"2 NaN NaN None None NaN NaN None \n",
|
1124 |
+
"3 NaN NaN None None NaN NaN None \n",
|
1125 |
+
"4 NaN NaN None None NaN NaN None \n",
|
1126 |
+
"5 NaN NaN None None NaN NaN None \n",
|
1127 |
+
"6 NaN NaN None None NaN NaN None \n",
|
1128 |
+
"7 NaN NaN None None NaN NaN None \n",
|
1129 |
+
"8 NaN NaN None None NaN NaN None \n",
|
1130 |
+
"9 NaN NaN None None NaN NaN None "
|
1131 |
+
]
|
1132 |
+
},
|
1133 |
+
"execution_count": 13,
|
1134 |
+
"metadata": {},
|
1135 |
+
"output_type": "execute_result"
|
1136 |
+
}
|
1137 |
+
],
|
1138 |
+
"source": [
|
1139 |
+
"data_df.head(10)"
|
1140 |
+
]
|
1141 |
+
},
|
1142 |
+
{
|
1143 |
+
"cell_type": "code",
|
1144 |
+
"execution_count": 16,
|
1145 |
+
"metadata": {},
|
1146 |
+
"outputs": [],
|
1147 |
+
"source": [
|
1148 |
+
"# write aa into jsonl format\n",
|
1149 |
+
"write_jsonl(aa, '/Users/alka/Devel/GIT_LFS_SKIP_SMUDGE=1/metadata/all/all_dataset.jsonl')"
|
1150 |
+
]
|
1151 |
+
},
|
1152 |
{
|
1153 |
"cell_type": "code",
|
1154 |
"execution_count": null,
|
data/csv/images_reviews_attributes.csv
ADDED
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
1 |
+
version https://git-lfs.github.com/spec/v1
|
2 |
+
oid sha256:52fa0b65c6c0c9d2030f7e6d893ee3be30b865da31346cd9cdfcb406c0983b74
|
3 |
+
size 146174207
|