|
156 | 156 | " {\n",
|
157 | 157 | " \"type\": \"filter\",\n",
|
158 | 158 | " \"operator\": \"=\",\n",
|
159 |
| - " \"columnIndex\": 7,\n", |
| 159 | + " \"column\": \"Origin\",\n", |
160 | 160 | " \"value\": \"Europe\",\n",
|
161 | 161 | " },\n",
|
162 |
| - " {\"type\": \"sort\", \"columnIndex\": 3, \"desc\": True},\n", |
| 162 | + " {\"type\": \"sort\", \"column\": \"Horsepower\", \"desc\": True},\n", |
163 | 163 | " ]\n",
|
164 | 164 | ")"
|
165 | 165 | ]
|
|
181 | 181 | "source": [
|
182 | 182 | "datagrid.transform(\n",
|
183 | 183 | " [\n",
|
184 |
| - " {\"type\": \"filter\", \"operator\": \"=\", \"columnIndex\": 7, \"value\": \"USA\"},\n", |
185 |
| - " {\"type\": \"filter\", \"operator\": \"<\", \"columnIndex\": 1, \"value\": 13},\n", |
186 |
| - " {\"type\": \"sort\", \"columnIndex\": 1},\n", |
| 184 | + " {\"type\": \"filter\", \"operator\": \"=\", \"column\": \"Origin\", \"value\": \"USA\"},\n", |
| 185 | + " {\"type\": \"filter\", \"operator\": \"<\", \"column\": \"Horsepower\", \"value\": 130},\n", |
| 186 | + " {\"type\": \"sort\", \"column\": \"Acceleration\"},\n", |
187 | 187 | " ]\n",
|
188 | 188 | ")"
|
189 | 189 | ]
|
|
372 | 372 | "name": "python",
|
373 | 373 | "nbconvert_exporter": "python",
|
374 | 374 | "pygments_lexer": "ipython3",
|
375 |
| - "version": "3.12.1" |
| 375 | + "version": "3.12.3" |
376 | 376 | }
|
377 | 377 | },
|
378 | 378 | "nbformat": 4,
|
|
0 commit comments