broke and fixed it; scaler fixed; dataset.csv is not saved; nice
Browse files- __pycache__/data_api_calls.cpython-312.pyc +0 -0
- app.py +1 -2
- data_api_calls.py +3 -2
- dataset.csv +0 -9
- scalers/feature_scaler_NO2.joblib +2 -2
- scalers/feature_scaler_O3.joblib +2 -2
- src/data_loading.py +1 -1
- test.ipynb +694 -0
- test.py +3 -0
__pycache__/data_api_calls.cpython-312.pyc
CHANGED
|
Binary files a/__pycache__/data_api_calls.cpython-312.pyc and b/__pycache__/data_api_calls.cpython-312.pyc differ
|
|
|
app.py
CHANGED
|
@@ -16,8 +16,7 @@ st.set_page_config(
|
|
| 16 |
|
| 17 |
alt.themes.enable("dark")
|
| 18 |
|
| 19 |
-
get_data()
|
| 20 |
-
dataset = pd.read_csv("dataset.csv")
|
| 21 |
today = dataset.iloc[-1]
|
| 22 |
previous_day = dataset.iloc[-2]
|
| 23 |
prediction = run_model("O3", data=dataset)
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|
|
|
| 16 |
|
| 17 |
alt.themes.enable("dark")
|
| 18 |
|
| 19 |
+
dataset = get_data()
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|
|
|
| 20 |
today = dataset.iloc[-1]
|
| 21 |
previous_day = dataset.iloc[-2]
|
| 22 |
prediction = run_model("O3", data=dataset)
|
data_api_calls.py
CHANGED
|
@@ -153,7 +153,7 @@ def insert_pollution(NO2, O3, data):
|
|
| 153 |
while O3:
|
| 154 |
df.loc[start_index, 'O3'] = O3.pop()
|
| 155 |
start_index += 1
|
| 156 |
-
|
| 157 |
|
| 158 |
def weather_data():
|
| 159 |
today = date.today().isoformat()
|
|
@@ -186,5 +186,6 @@ def get_data():
|
|
| 186 |
NO2, O3 = clean_values()
|
| 187 |
df = add_columns()
|
| 188 |
scaled_df = scale(df)
|
| 189 |
-
insert_pollution(NO2, O3, scaled_df)
|
| 190 |
os.remove('weather_data.csv')
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|
|
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|
|
| 153 |
while O3:
|
| 154 |
df.loc[start_index, 'O3'] = O3.pop()
|
| 155 |
start_index += 1
|
| 156 |
+
return df
|
| 157 |
|
| 158 |
def weather_data():
|
| 159 |
today = date.today().isoformat()
|
|
|
|
| 186 |
NO2, O3 = clean_values()
|
| 187 |
df = add_columns()
|
| 188 |
scaled_df = scale(df)
|
| 189 |
+
output_df = insert_pollution(NO2, O3, scaled_df)
|
| 190 |
os.remove('weather_data.csv')
|
| 191 |
+
return output_df
|
dataset.csv
DELETED
|
@@ -1,9 +0,0 @@
|
|
| 1 |
-
date,NO2,O3,wind_speed,mean_temp,global_radiation,percipitation,pressure,minimum_visibility,humidity,weekday
|
| 2 |
-
2024-10-16,22.602711656441716,22.88128805620609,61,151,40,0,10103,358,82,Wednesday
|
| 3 |
-
2024-10-17,23.104327323162277,23.038637566137567,51,169,43,6,10100,371,86,Thursday
|
| 4 |
-
2024-10-18,23.68285714285714,23.71661094224924,21,156,42,39,10140,64,97,Friday
|
| 5 |
-
2024-10-19,24.532038834951457,23.604722719141325,43,147,43,28,10140,236,92,Saturday
|
| 6 |
-
2024-10-20,23.019101941747575,24.173377192982453,68,145,0,0,10160,241,82,Sunday
|
| 7 |
-
2024-10-21,21.275629139072848,25.05873563218391,58,144,27,43,10206,220,92,Monday
|
| 8 |
-
2024-10-22,22.334374999999998,24.5942194092827,76,123,57,12,10265,100,87,Tuesday
|
| 9 |
-
2024-10-23,24.261733333333336,23.56,31,115,7,0,10328,105,95,Wednesday
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scalers/feature_scaler_NO2.joblib
CHANGED
|
@@ -1,3 +1,3 @@
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| 1 |
version https://git-lfs.github.com/spec/v1
|
| 2 |
-
oid sha256:
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| 3 |
-
size
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| 1 |
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:6281e460d3a5a83a3d6a240aa76c26e45bd15089364b88d3a26fd638536a30b5
|
| 3 |
+
size 5791
|
scalers/feature_scaler_O3.joblib
CHANGED
|
@@ -1,3 +1,3 @@
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|
| 1 |
version https://git-lfs.github.com/spec/v1
|
| 2 |
-
oid sha256:
|
| 3 |
-
size
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| 1 |
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:d6e30fc2c7ce7a00bc1b8db08e5f4ffa110136a796f55a68beedb479b07189f7
|
| 3 |
+
size 5023
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src/data_loading.py
CHANGED
|
@@ -130,7 +130,7 @@ def create_features(
|
|
| 130 |
feature_scaler = joblib.load(f"scalers/feature_scaler_{target_particle}.joblib")
|
| 131 |
|
| 132 |
# Fit the scalers on the training data
|
| 133 |
-
X_scaled = feature_scaler.
|
| 134 |
|
| 135 |
# Convert scaled data back to DataFrame for consistency
|
| 136 |
X_scaled = pd.DataFrame(
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|
| 130 |
feature_scaler = joblib.load(f"scalers/feature_scaler_{target_particle}.joblib")
|
| 131 |
|
| 132 |
# Fit the scalers on the training data
|
| 133 |
+
X_scaled = feature_scaler.transform(x)
|
| 134 |
|
| 135 |
# Convert scaled data back to DataFrame for consistency
|
| 136 |
X_scaled = pd.DataFrame(
|
test.ipynb
ADDED
|
@@ -0,0 +1,694 @@
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"text": [
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"/Users/mihkelmariuszjezierski/anaconda3/envs/ml-industry/lib/python3.12/site-packages/tqdm/auto.py:21: TqdmWarning: IProgress not found. Please update jupyter and ipywidgets. See https://ipywidgets.readthedocs.io/en/stable/user_install.html\n",
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"source": [
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"from src.models_loading import run_model\n",
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"from data_api_calls import get_data\n",
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"metadata": {},
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"source": [
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"from src.data_loading import create_features"
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"metadata": {},
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"outputs": [],
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"source": [
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"metadata": {},
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"outputs": [],
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"source": [
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"data = pd.read_csv(\"dataset.csv\")\n",
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"target_particle = \"O3\""
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},
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"cell_type": "code",
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"execution_count": 4,
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"metadata": {},
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"outputs": [
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"data": {
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|
| 75 |
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" <thead>\n",
|
| 76 |
+
" <tr style=\"text-align: right;\">\n",
|
| 77 |
+
" <th></th>\n",
|
| 78 |
+
" <th>date</th>\n",
|
| 79 |
+
" <th>NO2</th>\n",
|
| 80 |
+
" <th>O3</th>\n",
|
| 81 |
+
" <th>wind_speed</th>\n",
|
| 82 |
+
" <th>mean_temp</th>\n",
|
| 83 |
+
" <th>global_radiation</th>\n",
|
| 84 |
+
" <th>percipitation</th>\n",
|
| 85 |
+
" <th>pressure</th>\n",
|
| 86 |
+
" <th>minimum_visibility</th>\n",
|
| 87 |
+
" <th>humidity</th>\n",
|
| 88 |
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" <th>weekday</th>\n",
|
| 89 |
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" </tr>\n",
|
| 90 |
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" </thead>\n",
|
| 91 |
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" <tbody>\n",
|
| 92 |
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" <tr>\n",
|
| 93 |
+
" <th>0</th>\n",
|
| 94 |
+
" <td>2024-10-16</td>\n",
|
| 95 |
+
" <td>22.602712</td>\n",
|
| 96 |
+
" <td>22.881288</td>\n",
|
| 97 |
+
" <td>61</td>\n",
|
| 98 |
+
" <td>151</td>\n",
|
| 99 |
+
" <td>40</td>\n",
|
| 100 |
+
" <td>0</td>\n",
|
| 101 |
+
" <td>10103</td>\n",
|
| 102 |
+
" <td>358</td>\n",
|
| 103 |
+
" <td>82</td>\n",
|
| 104 |
+
" <td>Wednesday</td>\n",
|
| 105 |
+
" </tr>\n",
|
| 106 |
+
" <tr>\n",
|
| 107 |
+
" <th>1</th>\n",
|
| 108 |
+
" <td>2024-10-17</td>\n",
|
| 109 |
+
" <td>23.104327</td>\n",
|
| 110 |
+
" <td>23.038638</td>\n",
|
| 111 |
+
" <td>51</td>\n",
|
| 112 |
+
" <td>169</td>\n",
|
| 113 |
+
" <td>43</td>\n",
|
| 114 |
+
" <td>6</td>\n",
|
| 115 |
+
" <td>10100</td>\n",
|
| 116 |
+
" <td>371</td>\n",
|
| 117 |
+
" <td>86</td>\n",
|
| 118 |
+
" <td>Thursday</td>\n",
|
| 119 |
+
" </tr>\n",
|
| 120 |
+
" <tr>\n",
|
| 121 |
+
" <th>2</th>\n",
|
| 122 |
+
" <td>2024-10-18</td>\n",
|
| 123 |
+
" <td>23.682857</td>\n",
|
| 124 |
+
" <td>23.716611</td>\n",
|
| 125 |
+
" <td>21</td>\n",
|
| 126 |
+
" <td>156</td>\n",
|
| 127 |
+
" <td>42</td>\n",
|
| 128 |
+
" <td>39</td>\n",
|
| 129 |
+
" <td>10140</td>\n",
|
| 130 |
+
" <td>64</td>\n",
|
| 131 |
+
" <td>97</td>\n",
|
| 132 |
+
" <td>Friday</td>\n",
|
| 133 |
+
" </tr>\n",
|
| 134 |
+
" <tr>\n",
|
| 135 |
+
" <th>3</th>\n",
|
| 136 |
+
" <td>2024-10-19</td>\n",
|
| 137 |
+
" <td>24.532039</td>\n",
|
| 138 |
+
" <td>23.604723</td>\n",
|
| 139 |
+
" <td>43</td>\n",
|
| 140 |
+
" <td>147</td>\n",
|
| 141 |
+
" <td>43</td>\n",
|
| 142 |
+
" <td>28</td>\n",
|
| 143 |
+
" <td>10140</td>\n",
|
| 144 |
+
" <td>236</td>\n",
|
| 145 |
+
" <td>92</td>\n",
|
| 146 |
+
" <td>Saturday</td>\n",
|
| 147 |
+
" </tr>\n",
|
| 148 |
+
" <tr>\n",
|
| 149 |
+
" <th>4</th>\n",
|
| 150 |
+
" <td>2024-10-20</td>\n",
|
| 151 |
+
" <td>23.019102</td>\n",
|
| 152 |
+
" <td>24.173377</td>\n",
|
| 153 |
+
" <td>68</td>\n",
|
| 154 |
+
" <td>145</td>\n",
|
| 155 |
+
" <td>0</td>\n",
|
| 156 |
+
" <td>0</td>\n",
|
| 157 |
+
" <td>10160</td>\n",
|
| 158 |
+
" <td>241</td>\n",
|
| 159 |
+
" <td>82</td>\n",
|
| 160 |
+
" <td>Sunday</td>\n",
|
| 161 |
+
" </tr>\n",
|
| 162 |
+
" <tr>\n",
|
| 163 |
+
" <th>5</th>\n",
|
| 164 |
+
" <td>2024-10-21</td>\n",
|
| 165 |
+
" <td>21.275629</td>\n",
|
| 166 |
+
" <td>25.058736</td>\n",
|
| 167 |
+
" <td>58</td>\n",
|
| 168 |
+
" <td>144</td>\n",
|
| 169 |
+
" <td>27</td>\n",
|
| 170 |
+
" <td>43</td>\n",
|
| 171 |
+
" <td>10206</td>\n",
|
| 172 |
+
" <td>220</td>\n",
|
| 173 |
+
" <td>92</td>\n",
|
| 174 |
+
" <td>Monday</td>\n",
|
| 175 |
+
" </tr>\n",
|
| 176 |
+
" <tr>\n",
|
| 177 |
+
" <th>6</th>\n",
|
| 178 |
+
" <td>2024-10-22</td>\n",
|
| 179 |
+
" <td>22.334375</td>\n",
|
| 180 |
+
" <td>24.594219</td>\n",
|
| 181 |
+
" <td>76</td>\n",
|
| 182 |
+
" <td>123</td>\n",
|
| 183 |
+
" <td>57</td>\n",
|
| 184 |
+
" <td>12</td>\n",
|
| 185 |
+
" <td>10265</td>\n",
|
| 186 |
+
" <td>100</td>\n",
|
| 187 |
+
" <td>87</td>\n",
|
| 188 |
+
" <td>Tuesday</td>\n",
|
| 189 |
+
" </tr>\n",
|
| 190 |
+
" <tr>\n",
|
| 191 |
+
" <th>7</th>\n",
|
| 192 |
+
" <td>2024-10-23</td>\n",
|
| 193 |
+
" <td>24.261733</td>\n",
|
| 194 |
+
" <td>23.560000</td>\n",
|
| 195 |
+
" <td>31</td>\n",
|
| 196 |
+
" <td>115</td>\n",
|
| 197 |
+
" <td>7</td>\n",
|
| 198 |
+
" <td>0</td>\n",
|
| 199 |
+
" <td>10328</td>\n",
|
| 200 |
+
" <td>105</td>\n",
|
| 201 |
+
" <td>95</td>\n",
|
| 202 |
+
" <td>Wednesday</td>\n",
|
| 203 |
+
" </tr>\n",
|
| 204 |
+
" </tbody>\n",
|
| 205 |
+
"</table>\n",
|
| 206 |
+
"</div>"
|
| 207 |
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],
|
| 208 |
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"text/plain": [
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| 209 |
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" date NO2 O3 wind_speed mean_temp global_radiation \\\n",
|
| 210 |
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"0 2024-10-16 22.602712 22.881288 61 151 40 \n",
|
| 211 |
+
"1 2024-10-17 23.104327 23.038638 51 169 43 \n",
|
| 212 |
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"2 2024-10-18 23.682857 23.716611 21 156 42 \n",
|
| 213 |
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"3 2024-10-19 24.532039 23.604723 43 147 43 \n",
|
| 214 |
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"4 2024-10-20 23.019102 24.173377 68 145 0 \n",
|
| 215 |
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"5 2024-10-21 21.275629 25.058736 58 144 27 \n",
|
| 216 |
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"6 2024-10-22 22.334375 24.594219 76 123 57 \n",
|
| 217 |
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"7 2024-10-23 24.261733 23.560000 31 115 7 \n",
|
| 218 |
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"\n",
|
| 219 |
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" percipitation pressure minimum_visibility humidity weekday \n",
|
| 220 |
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"0 0 10103 358 82 Wednesday \n",
|
| 221 |
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"1 6 10100 371 86 Thursday \n",
|
| 222 |
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|
| 223 |
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"3 28 10140 236 92 Saturday \n",
|
| 224 |
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"4 0 10160 241 82 Sunday \n",
|
| 225 |
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"5 43 10206 220 92 Monday \n",
|
| 226 |
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"6 12 10265 100 87 Tuesday \n",
|
| 227 |
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"7 0 10328 105 95 Wednesday "
|
| 228 |
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|
| 229 |
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| 230 |
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| 231 |
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| 244 |
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"text": [
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"source": [
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| 254 |
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| 255 |
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| 256 |
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" lag_days=7,\n",
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|
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| 286 |
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" <th></th>\n",
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| 287 |
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" <th>NO2</th>\n",
|
| 288 |
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" <th>O3</th>\n",
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| 289 |
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" <th>wind_speed</th>\n",
|
| 290 |
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" <th>mean_temp</th>\n",
|
| 291 |
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" <th>global_radiation</th>\n",
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| 292 |
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" <th>percipitation</th>\n",
|
| 293 |
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" <th>pressure</th>\n",
|
| 294 |
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" <th>minimum_visibility</th>\n",
|
| 295 |
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" <th>humidity</th>\n",
|
| 296 |
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" <th>weekday_sin</th>\n",
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| 297 |
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|
| 298 |
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" <th>O3_last_year_4_days_before</th>\n",
|
| 299 |
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" <th>NO2_last_year_4_days_before</th>\n",
|
| 300 |
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" <th>O3_last_year_5_days_before</th>\n",
|
| 301 |
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" <th>NO2_last_year_5_days_before</th>\n",
|
| 302 |
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" <th>O3_last_year_6_days_before</th>\n",
|
| 303 |
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" <th>NO2_last_year_6_days_before</th>\n",
|
| 304 |
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" <th>O3_last_year_7_days_before</th>\n",
|
| 305 |
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" <th>NO2_last_year_7_days_before</th>\n",
|
| 306 |
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" <th>O3_last_year_3_days_after</th>\n",
|
| 307 |
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" <th>NO2_last_year_3_days_after</th>\n",
|
| 308 |
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" </tr>\n",
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| 309 |
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" </thead>\n",
|
| 310 |
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" <tbody>\n",
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| 311 |
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" <tr>\n",
|
| 312 |
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" <th>0</th>\n",
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| 313 |
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| 314 |
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" <td>-0.855455</td>\n",
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| 315 |
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| 316 |
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| 318 |
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| 319 |
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" <td>1.783274</td>\n",
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| 320 |
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" <td>2.813837</td>\n",
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| 321 |
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" <td>1.547919</td>\n",
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| 322 |
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| 323 |
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" <td>...</td>\n",
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| 324 |
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" <td>-1.036205</td>\n",
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| 325 |
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" <td>-0.802392</td>\n",
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| 326 |
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" <td>-0.883032</td>\n",
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| 327 |
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" <td>-0.968984</td>\n",
|
| 328 |
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" <td>0.333776</td>\n",
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| 329 |
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" <td>-1.446199</td>\n",
|
| 330 |
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" <td>-1.180992</td>\n",
|
| 331 |
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" <td>-0.54567</td>\n",
|
| 332 |
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" <td>-1.15814</td>\n",
|
| 333 |
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" <td>-0.358079</td>\n",
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| 334 |
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" </tr>\n",
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| 335 |
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" </tbody>\n",
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| 336 |
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"</table>\n",
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| 337 |
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"<p>1 rows × 87 columns</p>\n",
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| 341 |
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" NO2 O3 wind_speed mean_temp global_radiation percipitation \\\n",
|
| 342 |
+
"0 -0.126371 -0.855455 -0.206181 0.082314 -1.330268 -0.493936 \n",
|
| 343 |
+
"\n",
|
| 344 |
+
" pressure minimum_visibility humidity weekday_sin ... \\\n",
|
| 345 |
+
"0 1.783274 2.813837 1.547919 1.37753 ... \n",
|
| 346 |
+
"\n",
|
| 347 |
+
" O3_last_year_4_days_before NO2_last_year_4_days_before \\\n",
|
| 348 |
+
"0 -1.036205 -0.802392 \n",
|
| 349 |
+
"\n",
|
| 350 |
+
" O3_last_year_5_days_before NO2_last_year_5_days_before \\\n",
|
| 351 |
+
"0 -0.883032 -0.968984 \n",
|
| 352 |
+
"\n",
|
| 353 |
+
" O3_last_year_6_days_before NO2_last_year_6_days_before \\\n",
|
| 354 |
+
"0 0.333776 -1.446199 \n",
|
| 355 |
+
"\n",
|
| 356 |
+
" O3_last_year_7_days_before NO2_last_year_7_days_before \\\n",
|
| 357 |
+
"0 -1.180992 -0.54567 \n",
|
| 358 |
+
"\n",
|
| 359 |
+
" O3_last_year_3_days_after NO2_last_year_3_days_after \n",
|
| 360 |
+
"0 -1.15814 -0.358079 \n",
|
| 361 |
+
"\n",
|
| 362 |
+
"[1 rows x 87 columns]"
|
| 363 |
+
]
|
| 364 |
+
},
|
| 365 |
+
"execution_count": 6,
|
| 366 |
+
"metadata": {},
|
| 367 |
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"output_type": "execute_result"
|
| 368 |
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}
|
| 369 |
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],
|
| 370 |
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"source": [
|
| 371 |
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"input_data"
|
| 372 |
+
]
|
| 373 |
+
},
|
| 374 |
+
{
|
| 375 |
+
"cell_type": "code",
|
| 376 |
+
"execution_count": null,
|
| 377 |
+
"metadata": {},
|
| 378 |
+
"outputs": [],
|
| 379 |
+
"source": [
|
| 380 |
+
"#prediction = run_model(particle=\"O3\", data=df)"
|
| 381 |
+
]
|
| 382 |
+
},
|
| 383 |
+
{
|
| 384 |
+
"cell_type": "code",
|
| 385 |
+
"execution_count": 9,
|
| 386 |
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"metadata": {},
|
| 387 |
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"outputs": [
|
| 388 |
+
{
|
| 389 |
+
"data": {
|
| 390 |
+
"text/html": [
|
| 391 |
+
"<div>\n",
|
| 392 |
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"<style scoped>\n",
|
| 393 |
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" .dataframe tbody tr th:only-of-type {\n",
|
| 394 |
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" vertical-align: middle;\n",
|
| 395 |
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" }\n",
|
| 396 |
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"\n",
|
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" }\n",
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"\n",
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" text-align: right;\n",
|
| 403 |
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|
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"</style>\n",
|
| 405 |
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"<table border=\"1\" class=\"dataframe\">\n",
|
| 406 |
+
" <thead>\n",
|
| 407 |
+
" <tr style=\"text-align: right;\">\n",
|
| 408 |
+
" <th></th>\n",
|
| 409 |
+
" <th>date</th>\n",
|
| 410 |
+
" <th>NO2</th>\n",
|
| 411 |
+
" <th>O3</th>\n",
|
| 412 |
+
" <th>wind_speed</th>\n",
|
| 413 |
+
" <th>mean_temp</th>\n",
|
| 414 |
+
" <th>global_radiation</th>\n",
|
| 415 |
+
" <th>percipitation</th>\n",
|
| 416 |
+
" <th>pressure</th>\n",
|
| 417 |
+
" <th>minimum_visibility</th>\n",
|
| 418 |
+
" <th>humidity</th>\n",
|
| 419 |
+
" <th>weekday</th>\n",
|
| 420 |
+
" </tr>\n",
|
| 421 |
+
" </thead>\n",
|
| 422 |
+
" <tbody>\n",
|
| 423 |
+
" <tr>\n",
|
| 424 |
+
" <th>0</th>\n",
|
| 425 |
+
" <td>2023-10-16</td>\n",
|
| 426 |
+
" <td>17.958784</td>\n",
|
| 427 |
+
" <td>32.611400</td>\n",
|
| 428 |
+
" <td>31</td>\n",
|
| 429 |
+
" <td>90</td>\n",
|
| 430 |
+
" <td>68</td>\n",
|
| 431 |
+
" <td>9</td>\n",
|
| 432 |
+
" <td>1022</td>\n",
|
| 433 |
+
" <td>348</td>\n",
|
| 434 |
+
" <td>88</td>\n",
|
| 435 |
+
" <td>Monday</td>\n",
|
| 436 |
+
" </tr>\n",
|
| 437 |
+
" <tr>\n",
|
| 438 |
+
" <th>1</th>\n",
|
| 439 |
+
" <td>2023-10-17</td>\n",
|
| 440 |
+
" <td>10.842703</td>\n",
|
| 441 |
+
" <td>39.812600</td>\n",
|
| 442 |
+
" <td>61</td>\n",
|
| 443 |
+
" <td>85</td>\n",
|
| 444 |
+
" <td>75</td>\n",
|
| 445 |
+
" <td>0</td>\n",
|
| 446 |
+
" <td>1019</td>\n",
|
| 447 |
+
" <td>348</td>\n",
|
| 448 |
+
" <td>84</td>\n",
|
| 449 |
+
" <td>Tuesday</td>\n",
|
| 450 |
+
" </tr>\n",
|
| 451 |
+
" <tr>\n",
|
| 452 |
+
" <th>2</th>\n",
|
| 453 |
+
" <td>2023-10-18</td>\n",
|
| 454 |
+
" <td>17.970267</td>\n",
|
| 455 |
+
" <td>31.779024</td>\n",
|
| 456 |
+
" <td>71</td>\n",
|
| 457 |
+
" <td>90</td>\n",
|
| 458 |
+
" <td>71</td>\n",
|
| 459 |
+
" <td>23</td>\n",
|
| 460 |
+
" <td>1006</td>\n",
|
| 461 |
+
" <td>238</td>\n",
|
| 462 |
+
" <td>77</td>\n",
|
| 463 |
+
" <td>Wednesday</td>\n",
|
| 464 |
+
" </tr>\n",
|
| 465 |
+
" <tr>\n",
|
| 466 |
+
" <th>3</th>\n",
|
| 467 |
+
" <td>2023-10-19</td>\n",
|
| 468 |
+
" <td>17.233056</td>\n",
|
| 469 |
+
" <td>18.715600</td>\n",
|
| 470 |
+
" <td>61</td>\n",
|
| 471 |
+
" <td>145</td>\n",
|
| 472 |
+
" <td>39</td>\n",
|
| 473 |
+
" <td>114</td>\n",
|
| 474 |
+
" <td>990</td>\n",
|
| 475 |
+
" <td>212</td>\n",
|
| 476 |
+
" <td>94</td>\n",
|
| 477 |
+
" <td>Thursday</td>\n",
|
| 478 |
+
" </tr>\n",
|
| 479 |
+
" <tr>\n",
|
| 480 |
+
" <th>4</th>\n",
|
| 481 |
+
" <td>2023-10-20</td>\n",
|
| 482 |
+
" <td>15.023600</td>\n",
|
| 483 |
+
" <td>22.040000</td>\n",
|
| 484 |
+
" <td>71</td>\n",
|
| 485 |
+
" <td>119</td>\n",
|
| 486 |
+
" <td>7</td>\n",
|
| 487 |
+
" <td>204</td>\n",
|
| 488 |
+
" <td>981</td>\n",
|
| 489 |
+
" <td>104</td>\n",
|
| 490 |
+
" <td>97</td>\n",
|
| 491 |
+
" <td>Friday</td>\n",
|
| 492 |
+
" </tr>\n",
|
| 493 |
+
" <tr>\n",
|
| 494 |
+
" <th>5</th>\n",
|
| 495 |
+
" <td>2023-10-21</td>\n",
|
| 496 |
+
" <td>8.723378</td>\n",
|
| 497 |
+
" <td>48.334400</td>\n",
|
| 498 |
+
" <td>61</td>\n",
|
| 499 |
+
" <td>131</td>\n",
|
| 500 |
+
" <td>39</td>\n",
|
| 501 |
+
" <td>35</td>\n",
|
| 502 |
+
" <td>989</td>\n",
|
| 503 |
+
" <td>277</td>\n",
|
| 504 |
+
" <td>88</td>\n",
|
| 505 |
+
" <td>Saturday</td>\n",
|
| 506 |
+
" </tr>\n",
|
| 507 |
+
" <tr>\n",
|
| 508 |
+
" <th>6</th>\n",
|
| 509 |
+
" <td>2023-10-22</td>\n",
|
| 510 |
+
" <td>20.634267</td>\n",
|
| 511 |
+
" <td>15.586000</td>\n",
|
| 512 |
+
" <td>71</td>\n",
|
| 513 |
+
" <td>121</td>\n",
|
| 514 |
+
" <td>55</td>\n",
|
| 515 |
+
" <td>39</td>\n",
|
| 516 |
+
" <td>1003</td>\n",
|
| 517 |
+
" <td>323</td>\n",
|
| 518 |
+
" <td>87</td>\n",
|
| 519 |
+
" <td>Sunday</td>\n",
|
| 520 |
+
" </tr>\n",
|
| 521 |
+
" <tr>\n",
|
| 522 |
+
" <th>7</th>\n",
|
| 523 |
+
" <td>2023-10-23</td>\n",
|
| 524 |
+
" <td>15.115600</td>\n",
|
| 525 |
+
" <td>24.628085</td>\n",
|
| 526 |
+
" <td>50</td>\n",
|
| 527 |
+
" <td>99</td>\n",
|
| 528 |
+
" <td>43</td>\n",
|
| 529 |
+
" <td>5</td>\n",
|
| 530 |
+
" <td>1011</td>\n",
|
| 531 |
+
" <td>59</td>\n",
|
| 532 |
+
" <td>95</td>\n",
|
| 533 |
+
" <td>Monday</td>\n",
|
| 534 |
+
" </tr>\n",
|
| 535 |
+
" <tr>\n",
|
| 536 |
+
" <th>8</th>\n",
|
| 537 |
+
" <td>2023-10-24</td>\n",
|
| 538 |
+
" <td>22.885676</td>\n",
|
| 539 |
+
" <td>27.117600</td>\n",
|
| 540 |
+
" <td>61</td>\n",
|
| 541 |
+
" <td>116</td>\n",
|
| 542 |
+
" <td>32</td>\n",
|
| 543 |
+
" <td>65</td>\n",
|
| 544 |
+
" <td>1001</td>\n",
|
| 545 |
+
" <td>231</td>\n",
|
| 546 |
+
" <td>92</td>\n",
|
| 547 |
+
" <td>Tuesday</td>\n",
|
| 548 |
+
" </tr>\n",
|
| 549 |
+
" <tr>\n",
|
| 550 |
+
" <th>9</th>\n",
|
| 551 |
+
" <td>2023-10-25</td>\n",
|
| 552 |
+
" <td>21.531757</td>\n",
|
| 553 |
+
" <td>13.321600</td>\n",
|
| 554 |
+
" <td>50</td>\n",
|
| 555 |
+
" <td>93</td>\n",
|
| 556 |
+
" <td>14</td>\n",
|
| 557 |
+
" <td>153</td>\n",
|
| 558 |
+
" <td>996</td>\n",
|
| 559 |
+
" <td>157</td>\n",
|
| 560 |
+
" <td>96</td>\n",
|
| 561 |
+
" <td>Wednesday</td>\n",
|
| 562 |
+
" </tr>\n",
|
| 563 |
+
" <tr>\n",
|
| 564 |
+
" <th>10</th>\n",
|
| 565 |
+
" <td>2023-10-26</td>\n",
|
| 566 |
+
" <td>23.072267</td>\n",
|
| 567 |
+
" <td>16.154167</td>\n",
|
| 568 |
+
" <td>31</td>\n",
|
| 569 |
+
" <td>94</td>\n",
|
| 570 |
+
" <td>36</td>\n",
|
| 571 |
+
" <td>1</td>\n",
|
| 572 |
+
" <td>995</td>\n",
|
| 573 |
+
" <td>48</td>\n",
|
| 574 |
+
" <td>97</td>\n",
|
| 575 |
+
" <td>Thursday</td>\n",
|
| 576 |
+
" </tr>\n",
|
| 577 |
+
" </tbody>\n",
|
| 578 |
+
"</table>\n",
|
| 579 |
+
"</div>"
|
| 580 |
+
],
|
| 581 |
+
"text/plain": [
|
| 582 |
+
" date NO2 O3 wind_speed mean_temp global_radiation \\\n",
|
| 583 |
+
"0 2023-10-16 17.958784 32.611400 31 90 68 \n",
|
| 584 |
+
"1 2023-10-17 10.842703 39.812600 61 85 75 \n",
|
| 585 |
+
"2 2023-10-18 17.970267 31.779024 71 90 71 \n",
|
| 586 |
+
"3 2023-10-19 17.233056 18.715600 61 145 39 \n",
|
| 587 |
+
"4 2023-10-20 15.023600 22.040000 71 119 7 \n",
|
| 588 |
+
"5 2023-10-21 8.723378 48.334400 61 131 39 \n",
|
| 589 |
+
"6 2023-10-22 20.634267 15.586000 71 121 55 \n",
|
| 590 |
+
"7 2023-10-23 15.115600 24.628085 50 99 43 \n",
|
| 591 |
+
"8 2023-10-24 22.885676 27.117600 61 116 32 \n",
|
| 592 |
+
"9 2023-10-25 21.531757 13.321600 50 93 14 \n",
|
| 593 |
+
"10 2023-10-26 23.072267 16.154167 31 94 36 \n",
|
| 594 |
+
"\n",
|
| 595 |
+
" percipitation pressure minimum_visibility humidity weekday \n",
|
| 596 |
+
"0 9 1022 348 88 Monday \n",
|
| 597 |
+
"1 0 1019 348 84 Tuesday \n",
|
| 598 |
+
"2 23 1006 238 77 Wednesday \n",
|
| 599 |
+
"3 114 990 212 94 Thursday \n",
|
| 600 |
+
"4 204 981 104 97 Friday \n",
|
| 601 |
+
"5 35 989 277 88 Saturday \n",
|
| 602 |
+
"6 39 1003 323 87 Sunday \n",
|
| 603 |
+
"7 5 1011 59 95 Monday \n",
|
| 604 |
+
"8 65 1001 231 92 Tuesday \n",
|
| 605 |
+
"9 153 996 157 96 Wednesday \n",
|
| 606 |
+
"10 1 995 48 97 Thursday "
|
| 607 |
+
]
|
| 608 |
+
},
|
| 609 |
+
"execution_count": 9,
|
| 610 |
+
"metadata": {},
|
| 611 |
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"output_type": "execute_result"
|
| 612 |
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}
|
| 613 |
+
],
|
| 614 |
+
"source": [
|
| 615 |
+
"get_past_data()"
|
| 616 |
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]
|
| 617 |
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},
|
| 618 |
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{
|
| 619 |
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"cell_type": "code",
|
| 620 |
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"execution_count": 9,
|
| 621 |
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"metadata": {},
|
| 622 |
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"outputs": [
|
| 623 |
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{
|
| 624 |
+
"name": "stderr",
|
| 625 |
+
"output_type": "stream",
|
| 626 |
+
"text": [
|
| 627 |
+
"2024-10-23 19:40:20.321 Thread 'MainThread': missing ScriptRunContext! This warning can be ignored when running in bare mode.\n",
|
| 628 |
+
"2024-10-23 19:40:20.322 Thread 'MainThread': missing ScriptRunContext! This warning can be ignored when running in bare mode.\n",
|
| 629 |
+
"2024-10-23 19:40:20.323 Thread 'MainThread': missing ScriptRunContext! This warning can be ignored when running in bare mode.\n"
|
| 630 |
+
]
|
| 631 |
+
},
|
| 632 |
+
{
|
| 633 |
+
"name": "stdout",
|
| 634 |
+
"output_type": "stream",
|
| 635 |
+
"text": [
|
| 636 |
+
"Number of rows with missing values dropped: 7\n"
|
| 637 |
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]
|
| 638 |
+
},
|
| 639 |
+
{
|
| 640 |
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"name": "stderr",
|
| 641 |
+
"output_type": "stream",
|
| 642 |
+
"text": [
|
| 643 |
+
"2024-10-23 19:40:34.183 Thread 'MainThread': missing ScriptRunContext! This warning can be ignored when running in bare mode.\n",
|
| 644 |
+
"2024-10-23 19:40:34.184 Thread 'MainThread': missing ScriptRunContext! This warning can be ignored when running in bare mode.\n"
|
| 645 |
+
]
|
| 646 |
+
}
|
| 647 |
+
],
|
| 648 |
+
"source": [
|
| 649 |
+
"prediction=run_model(particle=target_particle, data=data)"
|
| 650 |
+
]
|
| 651 |
+
},
|
| 652 |
+
{
|
| 653 |
+
"cell_type": "code",
|
| 654 |
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"execution_count": 10,
|
| 655 |
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"metadata": {},
|
| 656 |
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"outputs": [
|
| 657 |
+
{
|
| 658 |
+
"data": {
|
| 659 |
+
"text/plain": [
|
| 660 |
+
"array([[19.90814701, 8.8039613 , 26.57711386]])"
|
| 661 |
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]
|
| 662 |
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},
|
| 663 |
+
"execution_count": 10,
|
| 664 |
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"metadata": {},
|
| 665 |
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"output_type": "execute_result"
|
| 666 |
+
}
|
| 667 |
+
],
|
| 668 |
+
"source": [
|
| 669 |
+
"prediction"
|
| 670 |
+
]
|
| 671 |
+
}
|
| 672 |
+
],
|
| 673 |
+
"metadata": {
|
| 674 |
+
"kernelspec": {
|
| 675 |
+
"display_name": "ml-industry",
|
| 676 |
+
"language": "python",
|
| 677 |
+
"name": "python3"
|
| 678 |
+
},
|
| 679 |
+
"language_info": {
|
| 680 |
+
"codemirror_mode": {
|
| 681 |
+
"name": "ipython",
|
| 682 |
+
"version": 3
|
| 683 |
+
},
|
| 684 |
+
"file_extension": ".py",
|
| 685 |
+
"mimetype": "text/x-python",
|
| 686 |
+
"name": "python",
|
| 687 |
+
"nbconvert_exporter": "python",
|
| 688 |
+
"pygments_lexer": "ipython3",
|
| 689 |
+
"version": "3.12.5"
|
| 690 |
+
}
|
| 691 |
+
},
|
| 692 |
+
"nbformat": 4,
|
| 693 |
+
"nbformat_minor": 2
|
| 694 |
+
}
|
test.py
ADDED
|
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
from models_loading import run_model
|
| 2 |
+
|
| 3 |
+
|