8787 "cell_type" : " markdown" ,
8888 "metadata" : {},
8989 "source" : [
90- " Once we have a report object, we can show it in the notebook:"
91- ]
92- },
93- {
94- "cell_type" : " code" ,
95- "execution_count" : null ,
96- "metadata" : {
97- "pycharm" : {
98- "name" : " #%%\n "
99- }
100- },
101- "outputs" : [],
102- "source" : [
103- " report"
104- ]
105- },
106- {
107- "cell_type" : " markdown" ,
108- "metadata" : {},
109- "source" : [
110- " Or we want to open the report in browser:"
90+ " Once we have a report object, we can show it in the notebook, or open the report in browser:"
11191 ]
11292 },
11393 {
120100 },
121101 "outputs" : [],
122102 "source" : [
103+ " # display(report)\n " ,
123104 " report.show_browser()"
124105 ]
125106 },
140121 },
141122 "outputs" : [],
142123 "source" : [
143- " report.save(filename= 'report.html')"
124+ " report.save('report.html')"
144125 ]
145126 },
146127 {
224205 },
225206 {
226207 "cell_type" : " code" ,
227- "execution_count" : 31 ,
208+ "execution_count" : null ,
228209 "metadata" : {
229210 "scrolled" : false
230211 },
231- "outputs" : [
232- {
233- "data" : {
234- "text/html" : [
235- " <iframe src=\" ../../_static/images/create_report/overview.html\" height=\" 345\" width=\" 80%\" style=\" border: 0\" ></iframe>\n "
236- ],
237- "text/plain" : [
238- " <IPython.core.display.HTML object>"
239- ]
240- },
241- "metadata" : {},
242- "output_type" : " display_data"
243- }
244- ],
212+ "outputs" : [],
245213 "source" : [
246- " %%html\n " ,
247- " <iframe src=\" ../../_static/images/create_report/overview.html\" height=\" 345\" width=\" 80%\" style=\" border: 0\" ></iframe>"
214+ " create_report(df, display=['Overview'])"
248215 ]
249216 },
250217 {
264231 " \n " ,
265232 " For categorical variable, the report shows text analysis, bar chart, pie chart, word cloud, word frequencies and word length.\n " ,
266233 " \n " ,
267- " For datetime variable, the report shows line chart"
268- ]
269- },
270- {
271- "cell_type" : " code" ,
272- "execution_count" : 30 ,
273- "metadata" : {},
274- "outputs" : [
275- {
276- "data" : {
277- "text/html" : [
278- " <iframe src=\" ../../_static/images/create_report/variables_num.html\" height=\" 275\" width=\" 80%\" style=\" border: 0\" ></iframe>\n "
279- ],
280- "text/plain" : [
281- " <IPython.core.display.HTML object>"
282- ]
283- },
284- "metadata" : {},
285- "output_type" : " display_data"
286- }
287- ],
288- "source" : [
289- " %%html\n " ,
290- " <iframe src=\" ../../_static/images/create_report/variables_num.html\" height=\" 275\" width=\" 80%\" style=\" border: 0\" ></iframe>"
291- ]
292- },
293- {
294- "cell_type" : " code" ,
295- "execution_count" : 29 ,
296- "metadata" : {},
297- "outputs" : [
298- {
299- "data" : {
300- "text/html" : [
301- " <iframe src=\" ../../_static/images/create_report/variables_cat.html\" height=\" 275\" width=\" 80%\" style=\" border: 0\" ></iframe>\n "
302- ],
303- "text/plain" : [
304- " <IPython.core.display.HTML object>"
305- ]
306- },
307- "metadata" : {},
308- "output_type" : " display_data"
309- }
310- ],
311- "source" : [
312- " %%html\n " ,
313- " <iframe src=\" ../../_static/images/create_report/variables_cat.html\" height=\" 275\" width=\" 80%\" style=\" border: 0\" ></iframe>"
314- ]
315- },
316- {
317- "cell_type" : " markdown" ,
318- "metadata" : {},
319- "source" : [
320- " The variables being displayed can also be sorted based on a number of criteria."
234+ " For datetime variable, the report shows line chart.\n " ,
235+ " \n " ,
236+ " Furthermore, the variables being displayed can also be sorted based on a number of criteria."
321237 ]
322238 },
323239 {
324240 "cell_type" : " code" ,
325- "execution_count" : 33 ,
241+ "execution_count" : null ,
326242 "metadata" : {},
327- "outputs" : [
328- {
329- "data" : {
330- "text/html" : [
331- " <iframe src=\" ../../_static/images/create_report/variables_sort.html\" height=\" 625\" width=\" 90%\" style=\" border: 0\" ></iframe>\n "
332- ],
333- "text/plain" : [
334- " <IPython.core.display.HTML object>"
335- ]
336- },
337- "metadata" : {},
338- "output_type" : " display_data"
339- }
340- ],
243+ "outputs" : [],
341244 "source" : [
342- " %%html\n " ,
343- " <iframe src=\" ../../_static/images/create_report/variables_sort.html\" height=\" 625\" width=\" 90%\" style=\" border: 0\" ></iframe>"
245+ " create_report(df, display=['Variables'])"
344246 ]
345247 },
346248 {
361263 },
362264 {
363265 "cell_type" : " code" ,
364- "execution_count" : 36 ,
266+ "execution_count" : null ,
365267 "metadata" : {},
366- "outputs" : [
367- {
368- "data" : {
369- "text/html" : [
370- " <iframe src=\" ../../_static/images/create_report/interactions.html\" height=\" 625\" width=\" 80%\" style=\" border: 0\" ></iframe>\n "
371- ],
372- "text/plain" : [
373- " <IPython.core.display.HTML object>"
374- ]
375- },
376- "metadata" : {},
377- "output_type" : " display_data"
378- }
379- ],
268+ "outputs" : [],
380269 "source" : [
381- " %%html\n " ,
382- " <iframe src=\" ../../_static/images/create_report/interactions.html\" height=\" 625\" width=\" 80%\" style=\" border: 0\" ></iframe>"
270+ " create_report(df, display=['Interactions'])"
383271 ]
384272 },
385273 {
389277 " You can also enable categorical variables by setting `interactions.cat_enable` to True. It will add categorical-categorical and categorical-numerical interactions:"
390278 ]
391279 },
392- {
393- "cell_type" : " code" ,
394- "execution_count" : null ,
395- "metadata" : {
396- "scrolled" : true
397- },
398- "outputs" : [],
399- "source" : [
400- " report = create_report(df, config={'interactions.cat_enable': True})"
401- ]
402- },
403280 {
404281 "cell_type" : " markdown" ,
405282 "metadata" : {},
416293 },
417294 {
418295 "cell_type" : " code" ,
419- "execution_count" : 37 ,
296+ "execution_count" : null ,
420297 "metadata" : {},
421- "outputs" : [
422- {
423- "data" : {
424- "text/html" : [
425- " <iframe src=\" ../../_static/images/create_report/correlations.html\" height=\" 530\" width=\" 80%\" style=\" border: 0\" ></iframe>\n "
426- ],
427- "text/plain" : [
428- " <IPython.core.display.HTML object>"
429- ]
430- },
431- "metadata" : {},
432- "output_type" : " display_data"
433- }
434- ],
298+ "outputs" : [],
435299 "source" : [
436- " %%html\n " ,
437- " <iframe src=\" ../../_static/images/create_report/correlations.html\" height=\" 530\" width=\" 80%\" style=\" border: 0\" ></iframe>"
300+ " create_report(df, display=['Correlations'])"
438301 ]
439302 },
440303 {
453316 },
454317 {
455318 "cell_type" : " code" ,
456- "execution_count" : 38 ,
319+ "execution_count" : null ,
457320 "metadata" : {},
458- "outputs" : [
459- {
460- "data" : {
461- "text/html" : [
462- " <iframe src=\" ../../_static/images/create_report/missing.html\" height=\" 530\" width=\" 80%\" style=\" border: 0\" ></iframe>\n "
463- ],
464- "text/plain" : [
465- " <IPython.core.display.HTML object>"
466- ]
467- },
468- "metadata" : {},
469- "output_type" : " display_data"
470- }
471- ],
321+ "outputs" : [],
472322 "source" : [
473- " %%html\n " ,
474- " <iframe src=\" ../../_static/images/create_report/missing.html\" height=\" 530\" width=\" 80%\" style=\" border: 0\" ></iframe>"
323+ " create_report(df, display=['Missing Values'])"
475324 ]
476325 }
477326 ],
491340 "name" : " python" ,
492341 "nbconvert_exporter" : " python" ,
493342 "pygments_lexer" : " ipython3" ,
494- "version" : " 3.8.9 "
343+ "version" : " 3.7.3 "
495344 }
496345 },
497346 "nbformat" : 4 ,
498347 "nbformat_minor" : 1
499- }
348+ }
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