Format: application/octet-stream
1 {
2 "cells": [
3 {
4 "cell_type": "code",
5 "execution_count": 1,
6 "id": "4a5ca34c",
7 "metadata": {},
8 "outputs": [],
9 "source": [
10 "import pandas as pd"
11 ]
12 },
13 {
14 "cell_type": "code",
15 "execution_count": 27,
16 "id": "f3029fdc",
17 "metadata": {},
18 "outputs": [],
19 "source": [
20 "wb= pd.read_csv('API_NY.GDP.MKTP.CD_DS2_en_csv_v2_2445719.csv', skiprows=4)\n",
21 "sc= pd.read_excel('scimagojr country rank 1996-2020.xlsx',index_col= 'Country')\n",
22 "ei= pd.read_excel('energy Indicators.xls',skiprows=17, skipfooter=38)"
23 ]
24 },
25 {
26 "cell_type": "code",
27 "execution_count": 3,
28 "id": "2e4b47f4",
29 "metadata": {},
30 "outputs": [
31 {
32 "data": {
33 "text/html": [
34 "<div>\n",
35 "<style scoped>\n",
36 " .dataframe tbody tr th:only-of-type {\n",
37 " vertical-align: middle;\n",
38 " }\n",
39 "\n",
40 " .dataframe tbody tr th {\n",
41 " vertical-align: top;\n",
42 " }\n",
43 "\n",
44 " .dataframe thead th {\n",
45 " text-align: right;\n",
46 " }\n",
47 "</style>\n",
48 "<table border=\"1\" class=\"dataframe\">\n",
49 " <thead>\n",
50 " <tr style=\"text-align: right;\">\n",
51 " <th></th>\n",
52 " <th>Unnamed: 0</th>\n",
53 " <th>Unnamed: 1</th>\n",
54 " <th>Unnamed: 2</th>\n",
55 " <th>Petajoules</th>\n",
56 " <th>Gigajoules</th>\n",
57 " <th>%</th>\n",
58 " </tr>\n",
59 " </thead>\n",
60 " <tbody>\n",
61 " <tr>\n",
62 " <th>0</th>\n",
63 " <td>NaN</td>\n",
64 " <td>Afghanistan</td>\n",
65 " <td>Afghanistan</td>\n",
66 " <td>321</td>\n",
67 " <td>10</td>\n",
68 " <td>78.669280</td>\n",
69 " </tr>\n",
70 " <tr>\n",
71 " <th>1</th>\n",
72 " <td>NaN</td>\n",
73 " <td>Albania</td>\n",
74 " <td>Albania</td>\n",
75 " <td>102</td>\n",
76 " <td>35</td>\n",
77 " <td>100.000000</td>\n",
78 " </tr>\n",
79 " <tr>\n",
80 " <th>2</th>\n",
81 " <td>NaN</td>\n",
82 " <td>Algeria</td>\n",
83 " <td>Algeria</td>\n",
84 " <td>1959</td>\n",
85 " <td>51</td>\n",
86 " <td>0.551010</td>\n",
87 " </tr>\n",
88 " <tr>\n",
89 " <th>3</th>\n",
90 " <td>NaN</td>\n",
91 " <td>American Samoa</td>\n",
92 " <td>American Samoa</td>\n",
93 " <td>...</td>\n",
94 " <td>...</td>\n",
95 " <td>0.641026</td>\n",
96 " </tr>\n",
97 " <tr>\n",
98 " <th>4</th>\n",
99 " <td>NaN</td>\n",
100 " <td>Andorra</td>\n",
101 " <td>Andorra</td>\n",
102 " <td>9</td>\n",
103 " <td>121</td>\n",
104 " <td>88.695650</td>\n",
105 " </tr>\n",
106 " <tr>\n",
107 " <th>...</th>\n",
108 " <td>...</td>\n",
109 " <td>...</td>\n",
110 " <td>...</td>\n",
111 " <td>...</td>\n",
112 " <td>...</td>\n",
113 " <td>...</td>\n",
114 " </tr>\n",
115 " <tr>\n",
116 " <th>222</th>\n",
117 " <td>NaN</td>\n",
118 " <td>Viet Nam</td>\n",
119 " <td>Viet Nam</td>\n",
120 " <td>2554</td>\n",
121 " <td>28</td>\n",
122 " <td>45.321520</td>\n",
123 " </tr>\n",
124 " <tr>\n",
125 " <th>223</th>\n",
126 " <td>NaN</td>\n",
127 " <td>Wallis and Futuna Islands</td>\n",
128 " <td>Wallis and Futuna Islands</td>\n",
129 " <td>0</td>\n",
130 " <td>26</td>\n",
131 " <td>0.000000</td>\n",
132 " </tr>\n",
133 " <tr>\n",
134 " <th>224</th>\n",
135 " <td>NaN</td>\n",
136 " <td>Yemen</td>\n",
137 " <td>Yemen</td>\n",
138 " <td>344</td>\n",
139 " <td>13</td>\n",
140 " <td>0.000000</td>\n",
141 " </tr>\n",
142 " <tr>\n",
143 " <th>225</th>\n",
144 " <td>NaN</td>\n",
145 " <td>Zambia</td>\n",
146 " <td>Zambia</td>\n",
147 " <td>400</td>\n",
148 " <td>26</td>\n",
149 " <td>99.714670</td>\n",
150 " </tr>\n",
151 " <tr>\n",
152 " <th>226</th>\n",
153 " <td>NaN</td>\n",
154 " <td>Zimbabwe</td>\n",
155 " <td>Zimbabwe</td>\n",
156 " <td>480</td>\n",
157 " <td>32</td>\n",
158 " <td>52.536120</td>\n",
159 " </tr>\n",
160 " </tbody>\n",
161 "</table>\n",
162 "<p>227 rows × 6 columns</p>\n",
163 "</div>"
164 ],
165 "text/plain": [
166 " Unnamed: 0 Unnamed: 1 Unnamed: 2 \\\n",
167 "0 NaN Afghanistan Afghanistan \n",
168 "1 NaN Albania Albania \n",
169 "2 NaN Algeria Algeria \n",
170 "3 NaN American Samoa American Samoa \n",
171 "4 NaN Andorra Andorra \n",
172 ".. ... ... ... \n",
173 "222 NaN Viet Nam Viet Nam \n",
174 "223 NaN Wallis and Futuna Islands Wallis and Futuna Islands \n",
175 "224 NaN Yemen Yemen \n",
176 "225 NaN Zambia Zambia \n",
177 "226 NaN Zimbabwe Zimbabwe \n",
178 "\n",
179 " Petajoules Gigajoules % \n",
180 "0 321 10 78.669280 \n",
181 "1 102 35 100.000000 \n",
182 "2 1959 51 0.551010 \n",
183 "3 ... ... 0.641026 \n",
184 "4 9 121 88.695650 \n",
185 ".. ... ... ... \n",
186 "222 2554 28 45.321520 \n",
187 "223 0 26 0.000000 \n",
188 "224 344 13 0.000000 \n",
189 "225 400 26 99.714670 \n",
190 "226 480 32 52.536120 \n",
191 "\n",
192 "[227 rows x 6 columns]"
193 ]
194 },
195 "execution_count": 3,
196 "metadata": {},
197 "output_type": "execute_result"
198 }
199 ],
200 "source": [
201 "ei"
202 ]
203 },
204 {
205 "cell_type": "code",
206 "execution_count": 4,
207 "id": "edd679d7",
208 "metadata": {},
209 "outputs": [],
210 "source": [
211 "columns= ['Rank', 'Documents', 'Citable documents', 'Citations', 'Self-citations', \\\n",
212 " 'Citations per document', 'H index', 'Energy Supply', 'Energy Supply per Capita', \\\n",
213 " '% Renewable', '2006', '2007', '2008', '2009', '2010', '2011', '2012', '2013', '2014', '2015']"
214 ]
215 },
216 {
217 "cell_type": "code",
218 "execution_count": 5,
219 "id": "794d9bdd",
220 "metadata": {},
221 "outputs": [],
222 "source": [
223 "replace=[\"Korea, Rep.\",\"Iran, Islamic Rep.\",\"Hong Kong SAR, China\"]\n",
224 "v= [\"South Korea\",\"Iran\",\"Hong Kong\"]\n",
225 "wb.replace(replace, v,inplace=True)"
226 ]
227 },
228 {
229 "cell_type": "code",
230 "execution_count": 8,
231 "id": "0079606a",
232 "metadata": {},
233 "outputs": [],
234 "source": [
235 "wb.set_axis?"
236 ]
237 },
238 {
239 "cell_type": "code",
240 "execution_count": 7,
241 "id": "35c8a614",
242 "metadata": {},
243 "outputs": [
244 {
245 "data": {
246 "text/html": [
247 "<div>\n",
248 "<style scoped>\n",
249 " .dataframe tbody tr th:only-of-type {\n",
250 " vertical-align: middle;\n",
251 " }\n",
252 "\n",
253 " .dataframe tbody tr th {\n",
254 " vertical-align: top;\n",
255 " }\n",
256 "\n",
257 " .dataframe thead th {\n",
258 " text-align: right;\n",
259 " }\n",
260 "</style>\n",
261 "<table border=\"1\" class=\"dataframe\">\n",
262 " <thead>\n",
263 " <tr style=\"text-align: right;\">\n",
264 " <th></th>\n",
265 " <th>Country Name</th>\n",
266 " <th>Country Code</th>\n",
267 " <th>Indicator Name</th>\n",
268 " <th>Indicator Code</th>\n",
269 " <th>1960</th>\n",
270 " <th>1961</th>\n",
271 " <th>1962</th>\n",
272 " <th>1963</th>\n",
273 " <th>1964</th>\n",
274 " <th>1965</th>\n",
275 " <th>...</th>\n",
276 " <th>2012</th>\n",
277 " <th>2013</th>\n",
278 " <th>2014</th>\n",
279 " <th>2015</th>\n",
280 " <th>2016</th>\n",
281 " <th>2017</th>\n",
282 " <th>2018</th>\n",
283 " <th>2019</th>\n",
284 " <th>2020</th>\n",
285 " <th>Unnamed: 65</th>\n",
286 " </tr>\n",
287 " <tr>\n",
288 " <th>Country Name</th>\n",
289 " <th></th>\n",
290 " <th></th>\n",
291 " <th></th>\n",
292 " <th></th>\n",
293 " <th></th>\n",
294 " <th></th>\n",
295 " <th></th>\n",
296 " <th></th>\n",
297 " <th></th>\n",
298 " <th></th>\n",
299 " <th></th>\n",
300 " <th></th>\n",
301 " <th></th>\n",
302 " <th></th>\n",
303 " <th></th>\n",
304 " <th></th>\n",
305 " <th></th>\n",
306 " <th></th>\n",
307 " <th></th>\n",
308 " <th></th>\n",
309 " <th></th>\n",
310 " </tr>\n",
311 " </thead>\n",
312 " <tbody>\n",
313 " <tr>\n",
314 " <th>Aruba</th>\n",
315 " <td>Aruba</td>\n",
316 " <td>ABW</td>\n",
317 " <td>GDP (current US$)</td>\n",
318 " <td>NY.GDP.MKTP.CD</td>\n",
319 " <td>NaN</td>\n",
320 " <td>NaN</td>\n",
321 " <td>NaN</td>\n",
322 " <td>NaN</td>\n",
323 " <td>NaN</td>\n",
324 " <td>NaN</td>\n",
325 " <td>...</td>\n",
326 " <td>2.534637e+09</td>\n",
327 " <td>2.701676e+09</td>\n",
328 " <td>2.765363e+09</td>\n",
329 " <td>2.919553e+09</td>\n",
330 " <td>2.965922e+09</td>\n",
331 " <td>3.056425e+09</td>\n",
332 " <td>NaN</td>\n",
333 " <td>NaN</td>\n",
334 " <td>NaN</td>\n",
335 " <td>NaN</td>\n",
336 " </tr>\n",
337 " <tr>\n",
338 " <th>Afghanistan</th>\n",
339 " <td>Afghanistan</td>\n",
340 " <td>AFG</td>\n",
341 " <td>GDP (current US$)</td>\n",
342 " <td>NY.GDP.MKTP.CD</td>\n",
343 " <td>5.377778e+08</td>\n",
344 " <td>5.488889e+08</td>\n",
345 " <td>5.466667e+08</td>\n",
346 " <td>7.511112e+08</td>\n",
347 " <td>8.000000e+08</td>\n",
348 " <td>1.006667e+09</td>\n",
349 " <td>...</td>\n",
350 " <td>2.000160e+10</td>\n",
351 " <td>2.056107e+10</td>\n",
352 " <td>2.048489e+10</td>\n",
353 " <td>1.990711e+10</td>\n",
354 " <td>1.801775e+10</td>\n",
355 " <td>1.886995e+10</td>\n",
356 " <td>1.835388e+10</td>\n",
357 " <td>1.929110e+10</td>\n",
358 " <td>NaN</td>\n",
359 " <td>NaN</td>\n",
360 " </tr>\n",
361 " <tr>\n",
362 " <th>Angola</th>\n",
363 " <td>Angola</td>\n",
364 " <td>AGO</td>\n",
365 " <td>GDP (current US$)</td>\n",
366 " <td>NY.GDP.MKTP.CD</td>\n",
367 " <td>NaN</td>\n",
368 " <td>NaN</td>\n",
369 " <td>NaN</td>\n",
370 " <td>NaN</td>\n",
371 " <td>NaN</td>\n",
372 " <td>NaN</td>\n",
373 " <td>...</td>\n",
374 " <td>1.280529e+11</td>\n",
375 " <td>1.367099e+11</td>\n",
376 " <td>1.457122e+11</td>\n",
377 " <td>1.161936e+11</td>\n",
378 " <td>1.011239e+11</td>\n",
379 " <td>1.221238e+11</td>\n",
380 " <td>1.013532e+11</td>\n",
381 " <td>8.881570e+10</td>\n",
382 " <td>NaN</td>\n",
383 " <td>NaN</td>\n",
384 " </tr>\n",
385 " <tr>\n",
386 " <th>Albania</th>\n",
387 " <td>Albania</td>\n",
388 " <td>ALB</td>\n",
389 " <td>GDP (current US$)</td>\n",
390 " <td>NY.GDP.MKTP.CD</td>\n",
391 " <td>NaN</td>\n",
392 " <td>NaN</td>\n",
393 " <td>NaN</td>\n",
394 " <td>NaN</td>\n",
395 " <td>NaN</td>\n",
396 " <td>NaN</td>\n",
397 " <td>...</td>\n",
398 " <td>1.231983e+10</td>\n",
399 " <td>1.277622e+10</td>\n",
400 " <td>1.322814e+10</td>\n",
401 " <td>1.138685e+10</td>\n",
402 " <td>1.186120e+10</td>\n",
403 " <td>1.301969e+10</td>\n",
404 " <td>1.514702e+10</td>\n",
405 " <td>1.527918e+10</td>\n",
406 " <td>NaN</td>\n",
407 " <td>NaN</td>\n",
408 " </tr>\n",
409 " <tr>\n",
410 " <th>Andorra</th>\n",
411 " <td>Andorra</td>\n",
412 " <td>AND</td>\n",
413 " <td>GDP (current US$)</td>\n",
414 " <td>NY.GDP.MKTP.CD</td>\n",
415 " <td>NaN</td>\n",
416 " <td>NaN</td>\n",
417 " <td>NaN</td>\n",
418 " <td>NaN</td>\n",
419 " <td>NaN</td>\n",
420 " <td>NaN</td>\n",
421 " <td>...</td>\n",
422 " <td>3.188809e+09</td>\n",
423 " <td>3.193704e+09</td>\n",
424 " <td>3.271808e+09</td>\n",
425 " <td>2.789870e+09</td>\n",
426 " <td>2.896679e+09</td>\n",
427 " <td>3.000181e+09</td>\n",
428 " <td>3.218316e+09</td>\n",
429 " <td>3.154058e+09</td>\n",
430 " <td>NaN</td>\n",
431 " <td>NaN</td>\n",
432 " </tr>\n",
433 " <tr>\n",
434 " <th>...</th>\n",
435 " <td>...</td>\n",
436 " <td>...</td>\n",
437 " <td>...</td>\n",
438 " <td>...</td>\n",
439 " <td>...</td>\n",
440 " <td>...</td>\n",
441 " <td>...</td>\n",
442 " <td>...</td>\n",
443 " <td>...</td>\n",
444 " <td>...</td>\n",
445 " <td>...</td>\n",
446 " <td>...</td>\n",
447 " <td>...</td>\n",
448 " <td>...</td>\n",
449 " <td>...</td>\n",
450 " <td>...</td>\n",
451 " <td>...</td>\n",
452 " <td>...</td>\n",
453 " <td>...</td>\n",
454 " <td>...</td>\n",
455 " <td>...</td>\n",
456 " </tr>\n",
457 " <tr>\n",
458 " <th>Kosovo</th>\n",
459 " <td>Kosovo</td>\n",
460 " <td>XKX</td>\n",
461 " <td>GDP (current US$)</td>\n",
462 " <td>NY.GDP.MKTP.CD</td>\n",
463 " <td>NaN</td>\n",
464 " <td>NaN</td>\n",
465 " <td>NaN</td>\n",
466 " <td>NaN</td>\n",
467 " <td>NaN</td>\n",
468 " <td>NaN</td>\n",
469 " <td>...</td>\n",
470 " <td>6.499807e+09</td>\n",
471 " <td>7.074778e+09</td>\n",
472 " <td>7.396705e+09</td>\n",
473 " <td>6.442916e+09</td>\n",
474 " <td>6.719172e+09</td>\n",
475 " <td>7.245707e+09</td>\n",
476 " <td>7.942962e+09</td>\n",
477 " <td>7.926134e+09</td>\n",
478 " <td>NaN</td>\n",
479 " <td>NaN</td>\n",
480 " </tr>\n",
481 " <tr>\n",
482 " <th>Yemen, Rep.</th>\n",
483 " <td>Yemen, Rep.</td>\n",
484 " <td>YEM</td>\n",
485 " <td>GDP (current US$)</td>\n",
486 " <td>NY.GDP.MKTP.CD</td>\n",
487 " <td>NaN</td>\n",
488 " <td>NaN</td>\n",
489 " <td>NaN</td>\n",
490 " <td>NaN</td>\n",
491 " <td>NaN</td>\n",
492 " <td>NaN</td>\n",
493 " <td>...</td>\n",
494 " <td>3.540134e+10</td>\n",
495 " <td>4.041524e+10</td>\n",
496 " <td>4.320647e+10</td>\n",
497 " <td>4.245062e+10</td>\n",
498 " <td>3.093598e+10</td>\n",
499 " <td>2.673614e+10</td>\n",
500 " <td>2.348627e+10</td>\n",
501 " <td>2.258108e+10</td>\n",
502 " <td>NaN</td>\n",
503 " <td>NaN</td>\n",
504 " </tr>\n",
505 " <tr>\n",
506 " <th>South Africa</th>\n",
507 " <td>South Africa</td>\n",
508 " <td>ZAF</td>\n",
509 " <td>GDP (current US$)</td>\n",
510 " <td>NY.GDP.MKTP.CD</td>\n",
511 " <td>7.575397e+09</td>\n",
512 " <td>7.972997e+09</td>\n",
513 " <td>8.497997e+09</td>\n",
514 " <td>9.423396e+09</td>\n",
515 " <td>1.037400e+10</td>\n",
516 " <td>1.133440e+10</td>\n",
517 " <td>...</td>\n",
518 " <td>3.963327e+11</td>\n",
519 " <td>3.668294e+11</td>\n",
520 " <td>3.509046e+11</td>\n",
521 " <td>3.176205e+11</td>\n",
522 " <td>2.963573e+11</td>\n",
523 " <td>3.495541e+11</td>\n",
524 " <td>3.682889e+11</td>\n",
525 " <td>3.514316e+11</td>\n",
526 " <td>NaN</td>\n",
527 " <td>NaN</td>\n",
528 " </tr>\n",
529 " <tr>\n",
530 " <th>Zambia</th>\n",
531 " <td>Zambia</td>\n",
532 " <td>ZMB</td>\n",
533 " <td>GDP (current US$)</td>\n",
534 " <td>NY.GDP.MKTP.CD</td>\n",
535 " <td>7.130000e+08</td>\n",
536 " <td>6.962857e+08</td>\n",
537 " <td>6.931429e+08</td>\n",
538 " <td>7.187143e+08</td>\n",
539 " <td>8.394286e+08</td>\n",
540 " <td>1.082857e+09</td>\n",
541 " <td>...</td>\n",
542 " <td>2.550306e+10</td>\n",
543 " <td>2.804555e+10</td>\n",
544 " <td>2.715073e+10</td>\n",
545 " <td>2.124334e+10</td>\n",
546 " <td>2.095475e+10</td>\n",
547 " <td>2.586817e+10</td>\n",
548 " <td>2.631214e+10</td>\n",
549 " <td>2.330977e+10</td>\n",
550 " <td>NaN</td>\n",
551 " <td>NaN</td>\n",
552 " </tr>\n",
553 " <tr>\n",
554 " <th>Zimbabwe</th>\n",
555 " <td>Zimbabwe</td>\n",
556 " <td>ZWE</td>\n",
557 " <td>GDP (current US$)</td>\n",
558 " <td>NY.GDP.MKTP.CD</td>\n",
559 " <td>1.052990e+09</td>\n",
560 " <td>1.096647e+09</td>\n",
561 " <td>1.117602e+09</td>\n",
562 " <td>1.159512e+09</td>\n",
563 " <td>1.217138e+09</td>\n",
564 " <td>1.311436e+09</td>\n",
565 " <td>...</td>\n",
566 " <td>1.711485e+10</td>\n",
567 " <td>1.909102e+10</td>\n",
568 " <td>1.949552e+10</td>\n",
569 " <td>1.996312e+10</td>\n",
570 " <td>2.054868e+10</td>\n",
571 " <td>2.204090e+10</td>\n",
572 " <td>2.431156e+10</td>\n",
573 " <td>2.144076e+10</td>\n",
574 " <td>NaN</td>\n",
575 " <td>NaN</td>\n",
576 " </tr>\n",
577 " </tbody>\n",
578 "</table>\n",
579 "<p>264 rows × 66 columns</p>\n",
580 "</div>"
581 ],
582 "text/plain": [
583 " Country Name Country Code Indicator Name Indicator Code \\\n",
584 "Country Name \n",
585 "Aruba Aruba ABW GDP (current US$) NY.GDP.MKTP.CD \n",
586 "Afghanistan Afghanistan AFG GDP (current US$) NY.GDP.MKTP.CD \n",
587 "Angola Angola AGO GDP (current US$) NY.GDP.MKTP.CD \n",
588 "Albania Albania ALB GDP (current US$) NY.GDP.MKTP.CD \n",
589 "Andorra Andorra AND GDP (current US$) NY.GDP.MKTP.CD \n",
590 "... ... ... ... ... \n",
591 "Kosovo Kosovo XKX GDP (current US$) NY.GDP.MKTP.CD \n",
592 "Yemen, Rep. Yemen, Rep. YEM GDP (current US$) NY.GDP.MKTP.CD \n",
593 "South Africa South Africa ZAF GDP (current US$) NY.GDP.MKTP.CD \n",
594 "Zambia Zambia ZMB GDP (current US$) NY.GDP.MKTP.CD \n",
595 "Zimbabwe Zimbabwe ZWE GDP (current US$) NY.GDP.MKTP.CD \n",
596 "\n",
597 " 1960 1961 1962 1963 \\\n",
598 "Country Name \n",
599 "Aruba NaN NaN NaN NaN \n",
600 "Afghanistan 5.377778e+08 5.488889e+08 5.466667e+08 7.511112e+08 \n",
601 "Angola NaN NaN NaN NaN \n",
602 "Albania NaN NaN NaN NaN \n",
603 "Andorra NaN NaN NaN NaN \n",
604 "... ... ... ... ... \n",
605 "Kosovo NaN NaN NaN NaN \n",
606 "Yemen, Rep. NaN NaN NaN NaN \n",
607 "South Africa 7.575397e+09 7.972997e+09 8.497997e+09 9.423396e+09 \n",
608 "Zambia 7.130000e+08 6.962857e+08 6.931429e+08 7.187143e+08 \n",
609 "Zimbabwe 1.052990e+09 1.096647e+09 1.117602e+09 1.159512e+09 \n",
610 "\n",
611 " 1964 1965 ... 2012 2013 \\\n",
612 "Country Name ... \n",
613 "Aruba NaN NaN ... 2.534637e+09 2.701676e+09 \n",
614 "Afghanistan 8.000000e+08 1.006667e+09 ... 2.000160e+10 2.056107e+10 \n",
615 "Angola NaN NaN ... 1.280529e+11 1.367099e+11 \n",
616 "Albania NaN NaN ... 1.231983e+10 1.277622e+10 \n",
617 "Andorra NaN NaN ... 3.188809e+09 3.193704e+09 \n",
618 "... ... ... ... ... ... \n",
619 "Kosovo NaN NaN ... 6.499807e+09 7.074778e+09 \n",
620 "Yemen, Rep. NaN NaN ... 3.540134e+10 4.041524e+10 \n",
621 "South Africa 1.037400e+10 1.133440e+10 ... 3.963327e+11 3.668294e+11 \n",
622 "Zambia 8.394286e+08 1.082857e+09 ... 2.550306e+10 2.804555e+10 \n",
623 "Zimbabwe 1.217138e+09 1.311436e+09 ... 1.711485e+10 1.909102e+10 \n",
624 "\n",
625 " 2014 2015 2016 2017 \\\n",
626 "Country Name \n",
627 "Aruba 2.765363e+09 2.919553e+09 2.965922e+09 3.056425e+09 \n",
628 "Afghanistan 2.048489e+10 1.990711e+10 1.801775e+10 1.886995e+10 \n",
629 "Angola 1.457122e+11 1.161936e+11 1.011239e+11 1.221238e+11 \n",
630 "Albania 1.322814e+10 1.138685e+10 1.186120e+10 1.301969e+10 \n",
631 "Andorra 3.271808e+09 2.789870e+09 2.896679e+09 3.000181e+09 \n",
632 "... ... ... ... ... \n",
633 "Kosovo 7.396705e+09 6.442916e+09 6.719172e+09 7.245707e+09 \n",
634 "Yemen, Rep. 4.320647e+10 4.245062e+10 3.093598e+10 2.673614e+10 \n",
635 "South Africa 3.509046e+11 3.176205e+11 2.963573e+11 3.495541e+11 \n",
636 "Zambia 2.715073e+10 2.124334e+10 2.095475e+10 2.586817e+10 \n",
637 "Zimbabwe 1.949552e+10 1.996312e+10 2.054868e+10 2.204090e+10 \n",
638 "\n",
639 " 2018 2019 2020 Unnamed: 65 \n",
640 "Country Name \n",
641 "Aruba NaN NaN NaN NaN \n",
642 "Afghanistan 1.835388e+10 1.929110e+10 NaN NaN \n",
643 "Angola 1.013532e+11 8.881570e+10 NaN NaN \n",
644 "Albania 1.514702e+10 1.527918e+10 NaN NaN \n",
645 "Andorra 3.218316e+09 3.154058e+09 NaN NaN \n",
646 "... ... ... ... ... \n",
647 "Kosovo 7.942962e+09 7.926134e+09 NaN NaN \n",
648 "Yemen, Rep. 2.348627e+10 2.258108e+10 NaN NaN \n",
649 "South Africa 3.682889e+11 3.514316e+11 NaN NaN \n",
650 "Zambia 2.631214e+10 2.330977e+10 NaN NaN \n",
651 "Zimbabwe 2.431156e+10 2.144076e+10 NaN NaN \n",
652 "\n",
653 "[264 rows x 66 columns]"
654 ]
655 },
656 "execution_count": 7,
657 "metadata": {},
658 "output_type": "execute_result"
659 }
660 ],
661 "source": [
662 "wb"
663 ]
664 },
665 {
666 "cell_type": "code",
667 "execution_count": 9,
668 "id": "7661f8ec",
669 "metadata": {},
670 "outputs": [
671 {
672 "data": {
673 "text/plain": [
674 "1484318219633.63"
675 ]
676 },
677 "execution_count": 9,
678 "metadata": {},
679 "output_type": "execute_result"
680 }
681 ],
682 "source": [
683 "wb['2014']['South Korea']"
684 ]
685 },
686 {
687 "cell_type": "code",
688 "execution_count": null,
689 "id": "e6e38db8",
690 "metadata": {},
691 "outputs": [],
692 "source": []
693 },
694 {
695 "cell_type": "code",
696 "execution_count": 10,
697 "id": "10d0f676",
698 "metadata": {},
699 "outputs": [],
700 "source": [
701 "ei.drop(['Unnamed: 0', 'Unnamed: 2'], axis =1, inplace=True)\n",
702 "ei.rename({'Unnamed: 1':'Country Name','Petajoules':'Energy Supply', 'Gigajoules':'Energy Supply per Capita',\\\n",
703 " '%':'% Renewable' },\n",
704 " axis=1, inplace=True)\n",
705 "to_replace= [\"Republic of Korea\",\"United States of America\",\"United Kingdom of Great Britain and Northern Ireland\",\\\n",
706 " \"China, Hong Kong Special Administrative Region\",'Iran (Islamic Republic of)']\n",
707 "values=[\"South Korea\",\"United States\",\"United Kingdom\",\"Hong Kong\", 'Iran']\n",
708 "ei.replace(to_replace, values, inplace=True)\n",
709 "ei['Energy Supply']= 1000000*ei['Energy Supply']\n",
710 "ei.set_axis(ei['Country Name'], inplace =True)"
711 ]
712 },
713 {
714 "cell_type": "code",
715 "execution_count": 11,
716 "id": "627e00aa",
717 "metadata": {},
718 "outputs": [
719 {
720 "data": {
721 "text/plain": [
722 "9172000000"
723 ]
724 },
725 "execution_count": 11,
726 "metadata": {},
727 "output_type": "execute_result"
728 }
729 ],
730 "source": [
731 "ei['Energy Supply'][\"Iran\"]"
732 ]
733 },
734 {
735 "cell_type": "code",
736 "execution_count": null,
737 "id": "96f51fa6",
738 "metadata": {},
739 "outputs": [],
740 "source": []
741 },
742 {
743 "cell_type": "code",
744 "execution_count": 12,
745 "id": "16691710",
746 "metadata": {},
747 "outputs": [],
748 "source": [
749 "sc.rename_axis('Country Name', inplace= True)"
750 ]
751 },
752 {
753 "cell_type": "code",
754 "execution_count": 13,
755 "id": "d1e956a6",
756 "metadata": {},
757 "outputs": [
758 {
759 "data": {
760 "text/html": [
761 "<div>\n",
762 "<style scoped>\n",
763 " .dataframe tbody tr th:only-of-type {\n",
764 " vertical-align: middle;\n",
765 " }\n",
766 "\n",
767 " .dataframe tbody tr th {\n",
768 " vertical-align: top;\n",
769 " }\n",
770 "\n",
771 " .dataframe thead th {\n",
772 " text-align: right;\n",
773 " }\n",
774 "</style>\n",
775 "<table border=\"1\" class=\"dataframe\">\n",
776 " <thead>\n",
777 " <tr style=\"text-align: right;\">\n",
778 " <th></th>\n",
779 " <th>Rank</th>\n",
780 " <th>Region</th>\n",
781 " <th>Documents</th>\n",
782 " <th>Citable documents</th>\n",
783 " <th>Citations</th>\n",
784 " <th>Self-citations</th>\n",
785 " <th>Citations per document</th>\n",
786 " <th>H index</th>\n",
787 " </tr>\n",
788 " <tr>\n",
789 " <th>Country Name</th>\n",
790 " <th></th>\n",
791 " <th></th>\n",
792 " <th></th>\n",
793 " <th></th>\n",
794 " <th></th>\n",
795 " <th></th>\n",
796 " <th></th>\n",
797 " <th></th>\n",
798 " </tr>\n",
799 " </thead>\n",
800 " <tbody>\n",
801 " <tr>\n",
802 " <th>China</th>\n",
803 " <td>1</td>\n",
804 " <td>Asiatic Region</td>\n",
805 " <td>273437</td>\n",
806 " <td>272374</td>\n",
807 " <td>2336764</td>\n",
808 " <td>1615239</td>\n",
809 " <td>8.55</td>\n",
810 " <td>245</td>\n",
811 " </tr>\n",
812 " <tr>\n",
813 " <th>United States</th>\n",
814 " <td>2</td>\n",
815 " <td>Northern America</td>\n",
816 " <td>175891</td>\n",
817 " <td>172431</td>\n",
818 " <td>2230544</td>\n",
819 " <td>724472</td>\n",
820 " <td>12.68</td>\n",
821 " <td>363</td>\n",
822 " </tr>\n",
823 " <tr>\n",
824 " <th>India</th>\n",
825 " <td>3</td>\n",
826 " <td>Asiatic Region</td>\n",
827 " <td>55082</td>\n",
828 " <td>53775</td>\n",
829 " <td>463165</td>\n",
830 " <td>162944</td>\n",
831 " <td>8.41</td>\n",
832 " <td>181</td>\n",
833 " </tr>\n",
834 " <tr>\n",
835 " <th>Japan</th>\n",
836 " <td>4</td>\n",
837 " <td>Asiatic Region</td>\n",
838 " <td>50523</td>\n",
839 " <td>50065</td>\n",
840 " <td>488062</td>\n",
841 " <td>119930</td>\n",
842 " <td>9.66</td>\n",
843 " <td>193</td>\n",
844 " </tr>\n",
845 " <tr>\n",
846 " <th>United Kingdom</th>\n",
847 " <td>5</td>\n",
848 " <td>Western Europe</td>\n",
849 " <td>43389</td>\n",
850 " <td>42284</td>\n",
851 " <td>615670</td>\n",
852 " <td>111290</td>\n",
853 " <td>14.19</td>\n",
854 " <td>226</td>\n",
855 " </tr>\n",
856 " <tr>\n",
857 " <th>Germany</th>\n",
858 " <td>6</td>\n",
859 " <td>Western Europe</td>\n",
860 " <td>38739</td>\n",
861 " <td>38013</td>\n",
862 " <td>433148</td>\n",
863 " <td>95145</td>\n",
864 " <td>11.18</td>\n",
865 " <td>196</td>\n",
866 " </tr>\n",
867 " <tr>\n",
868 " <th>Russian Federation</th>\n",
869 " <td>7</td>\n",
870 " <td>Eastern Europe</td>\n",
871 " <td>36735</td>\n",
872 " <td>36560</td>\n",
873 " <td>115938</td>\n",
874 " <td>54993</td>\n",
875 " <td>3.16</td>\n",
876 " <td>90</td>\n",
877 " </tr>\n",
878 " <tr>\n",
879 " <th>Canada</th>\n",
880 " <td>8</td>\n",
881 " <td>Northern America</td>\n",
882 " <td>33472</td>\n",
883 " <td>32863</td>\n",
884 " <td>568080</td>\n",
885 " <td>100953</td>\n",
886 " <td>16.97</td>\n",
887 " <td>227</td>\n",
888 " </tr>\n",
889 " <tr>\n",
890 " <th>Italy</th>\n",
891 " <td>9</td>\n",
892 " <td>Western Europe</td>\n",
893 " <td>27983</td>\n",
894 " <td>26940</td>\n",
895 " <td>352993</td>\n",
896 " <td>87828</td>\n",
897 " <td>12.61</td>\n",
898 " <td>166</td>\n",
899 " </tr>\n",
900 " <tr>\n",
901 " <th>South Korea</th>\n",
902 " <td>10</td>\n",
903 " <td>Asiatic Region</td>\n",
904 " <td>27655</td>\n",
905 " <td>27445</td>\n",
906 " <td>328488</td>\n",
907 " <td>61531</td>\n",
908 " <td>11.88</td>\n",
909 " <td>155</td>\n",
910 " </tr>\n",
911 " <tr>\n",
912 " <th>France</th>\n",
913 " <td>11</td>\n",
914 " <td>Western Europe</td>\n",
915 " <td>25232</td>\n",
916 " <td>24732</td>\n",
917 " <td>343860</td>\n",
918 " <td>65734</td>\n",
919 " <td>13.63</td>\n",
920 " <td>178</td>\n",
921 " </tr>\n",
922 " <tr>\n",
923 " <th>Iran</th>\n",
924 " <td>12</td>\n",
925 " <td>Middle East</td>\n",
926 " <td>22933</td>\n",
927 " <td>22734</td>\n",
928 " <td>307280</td>\n",
929 " <td>97038</td>\n",
930 " <td>13.40</td>\n",
931 " <td>141</td>\n",
932 " </tr>\n",
933 " <tr>\n",
934 " <th>Spain</th>\n",
935 " <td>13</td>\n",
936 " <td>Western Europe</td>\n",
937 " <td>21955</td>\n",
938 " <td>21597</td>\n",
939 " <td>352497</td>\n",
940 " <td>64588</td>\n",
941 " <td>16.06</td>\n",
942 " <td>176</td>\n",
943 " </tr>\n",
944 " <tr>\n",
945 " <th>Brazil</th>\n",
946 " <td>14</td>\n",
947 " <td>Latin America</td>\n",
948 " <td>21524</td>\n",
949 " <td>21236</td>\n",
950 " <td>183915</td>\n",
951 " <td>45172</td>\n",
952 " <td>8.54</td>\n",
953 " <td>127</td>\n",
954 " </tr>\n",
955 " <tr>\n",
956 " <th>Australia</th>\n",
957 " <td>15</td>\n",
958 " <td>Pacific Region</td>\n",
959 " <td>20614</td>\n",
960 " <td>20147</td>\n",
961 " <td>314307</td>\n",
962 " <td>51583</td>\n",
963 " <td>15.25</td>\n",
964 " <td>176</td>\n",
965 " </tr>\n",
966 " </tbody>\n",
967 "</table>\n",
968 "</div>"
969 ],
970 "text/plain": [
971 " Rank Region Documents Citable documents \\\n",
972 "Country Name \n",
973 "China 1 Asiatic Region 273437 272374 \n",
974 "United States 2 Northern America 175891 172431 \n",
975 "India 3 Asiatic Region 55082 53775 \n",
976 "Japan 4 Asiatic Region 50523 50065 \n",
977 "United Kingdom 5 Western Europe 43389 42284 \n",
978 "Germany 6 Western Europe 38739 38013 \n",
979 "Russian Federation 7 Eastern Europe 36735 36560 \n",
980 "Canada 8 Northern America 33472 32863 \n",
981 "Italy 9 Western Europe 27983 26940 \n",
982 "South Korea 10 Asiatic Region 27655 27445 \n",
983 "France 11 Western Europe 25232 24732 \n",
984 "Iran 12 Middle East 22933 22734 \n",
985 "Spain 13 Western Europe 21955 21597 \n",
986 "Brazil 14 Latin America 21524 21236 \n",
987 "Australia 15 Pacific Region 20614 20147 \n",
988 "\n",
989 " Citations Self-citations Citations per document H index \n",
990 "Country Name \n",
991 "China 2336764 1615239 8.55 245 \n",
992 "United States 2230544 724472 12.68 363 \n",
993 "India 463165 162944 8.41 181 \n",
994 "Japan 488062 119930 9.66 193 \n",
995 "United Kingdom 615670 111290 14.19 226 \n",
996 "Germany 433148 95145 11.18 196 \n",
997 "Russian Federation 115938 54993 3.16 90 \n",
998 "Canada 568080 100953 16.97 227 \n",
999 "Italy 352993 87828 12.61 166 \n",
1000 "South Korea 328488 61531 11.88 155 \n",
1001 "France 343860 65734 13.63 178 \n",
1002 "Iran 307280 97038 13.40 141 \n",
1003 "Spain 352497 64588 16.06 176 \n",
1004 "Brazil 183915 45172 8.54 127 \n",
1005 "Australia 314307 51583 15.25 176 "
1006 ]
1007 },
1008 "execution_count": 13,
1009 "metadata": {},
1010 "output_type": "execute_result"
1011 }
1012 ],
1013 "source": [
1014 "sc"
1015 ]
1016 },
1017 {
1018 "cell_type": "code",
1019 "execution_count": 14,
1020 "id": "b2663396",
1021 "metadata": {},
1022 "outputs": [],
1023 "source": [
1024 "frames=[wb,ei,sc]\n",
1025 "final= pd.concat(frames, axis=1)"
1026 ]
1027 },
1028 {
1029 "cell_type": "code",
1030 "execution_count": 15,
1031 "id": "9a9ca3f2",
1032 "metadata": {},
1033 "outputs": [],
1034 "source": [
1035 "final1=final[columns].sort_values('Rank')[:15]"
1036 ]
1037 },
1038 {
1039 "cell_type": "code",
1040 "execution_count": 16,
1041 "id": "240950f6",
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1044 {
1045 "data": {
1046 "text/plain": [
1047 "266298911661.144"
1048 ]
1049 },
1050 "execution_count": 16,
1051 "metadata": {},
1052 "output_type": "execute_result"
1053 }
1054 ],
1055 "source": [
1056 "final1['2006']['Iran']"
1057 ]
1058 },
1059 {
1060 "cell_type": "code",
1061 "execution_count": 17,
1062 "id": "7449b835",
1063 "metadata": {
1064 "scrolled": true
1065 },
1066 "outputs": [
1067 {
1068 "data": {
1069 "text/plain": [
1070 "(15, 20)"
1071 ]
1072 },
1073 "execution_count": 17,
1074 "metadata": {},
1075 "output_type": "execute_result"
1076 }
1077 ],
1078 "source": [
1079 "final1.shape"
1080 ]
1081 },
1082 {
1083 "cell_type": "code",
1084 "execution_count": 18,
1085 "id": "0f088206",
1086 "metadata": {},
1087 "outputs": [],
1088 "source": [
1089 "l=[127191000000.0,90838000000.0,18984000000.0,7920000000.0,30709000000.0,\n",
1090 "10431000000.0,13261000000.0,33195000000.0,10597000000.0,11007000000.0,\n",
1091 "6530000000.0,4923000000.0,9172000000.0,5386000000.0,12149000000.0]"
1092 ]
1093 },
1094 {
1095 "cell_type": "code",
1096 "execution_count": 19,
1097 "id": "6b625c52",
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1100 },
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1102 {
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1120 " <thead>\n",
1121 " <tr style=\"text-align: right;\">\n",
1122 " <th></th>\n",
1123 " <th>2006</th>\n",
1124 " <th>2007</th>\n",
1125 " <th>2008</th>\n",
1126 " <th>2009</th>\n",
1127 " <th>2010</th>\n",
1128 " <th>2011</th>\n",
1129 " <th>2012</th>\n",
1130 " <th>2013</th>\n",
1131 " <th>2014</th>\n",
1132 " <th>2015</th>\n",
1133 " </tr>\n",
1134 " <tr>\n",
1135 " <th>Country Name</th>\n",
1136 " <th></th>\n",
1137 " <th></th>\n",
1138 " <th></th>\n",
1139 " <th></th>\n",
1140 " <th></th>\n",
1141 " <th></th>\n",
1142 " <th></th>\n",
1143 " <th></th>\n",
1144 " <th></th>\n",
1145 " <th></th>\n",
1146 " </tr>\n",
1147 " </thead>\n",
1148 " <tbody>\n",
1149 " <tr>\n",
1150 " <th>China</th>\n",
1151 " <td>2.752132e+12</td>\n",
1152 " <td>3.550343e+12</td>\n",
1153 " <td>4.594307e+12</td>\n",
1154 " <td>5.101703e+12</td>\n",
1155 " <td>6.087164e+12</td>\n",
1156 " <td>7.551500e+12</td>\n",
1157 " <td>8.532230e+12</td>\n",
1158 " <td>9.570406e+12</td>\n",
1159 " <td>1.047568e+13</td>\n",
1160 " <td>1.106155e+13</td>\n",
1161 " </tr>\n",
1162 " <tr>\n",
1163 " <th>United States</th>\n",
1164 " <td>1.381461e+13</td>\n",
1165 " <td>1.445186e+13</td>\n",
1166 " <td>1.471284e+13</td>\n",
1167 " <td>1.444893e+13</td>\n",
1168 " <td>1.499205e+13</td>\n",
1169 " <td>1.554258e+13</td>\n",
1170 " <td>1.619701e+13</td>\n",
1171 " <td>1.678485e+13</td>\n",
1172 " <td>1.752716e+13</td>\n",
1173 " <td>1.822470e+13</td>\n",
1174 " </tr>\n",
1175 " <tr>\n",
1176 " <th>India</th>\n",
1177 " <td>9.402599e+11</td>\n",
1178 " <td>1.216735e+12</td>\n",
1179 " <td>1.198896e+12</td>\n",
1180 " <td>1.341887e+12</td>\n",
1181 " <td>1.675615e+12</td>\n",
1182 " <td>1.823050e+12</td>\n",
1183 " <td>1.827638e+12</td>\n",
1184 " <td>1.856722e+12</td>\n",
1185 " <td>2.039127e+12</td>\n",
1186 " <td>2.103588e+12</td>\n",
1187 " </tr>\n",
1188 " <tr>\n",
1189 " <th>Japan</th>\n",
1190 " <td>4.530377e+12</td>\n",
1191 " <td>4.515265e+12</td>\n",
1192 " <td>5.037908e+12</td>\n",
1193 " <td>5.231383e+12</td>\n",
1194 " <td>5.700098e+12</td>\n",
1195 " <td>6.157460e+12</td>\n",
1196 " <td>6.203213e+12</td>\n",
1197 " <td>5.155717e+12</td>\n",
1198 " <td>4.850414e+12</td>\n",
1199 " <td>4.389476e+12</td>\n",
1200 " </tr>\n",
1201 " <tr>\n",
1202 " <th>United Kingdom</th>\n",
1203 " <td>2.713750e+12</td>\n",
1204 " <td>3.100882e+12</td>\n",
1205 " <td>2.922667e+12</td>\n",
1206 " <td>2.410910e+12</td>\n",
1207 " <td>2.475244e+12</td>\n",
1208 " <td>2.659310e+12</td>\n",
1209 " <td>2.704888e+12</td>\n",
1210 " <td>2.786023e+12</td>\n",
1211 " <td>3.063803e+12</td>\n",
1212 " <td>2.928591e+12</td>\n",
1213 " </tr>\n",
1214 " <tr>\n",
1215 " <th>Germany</th>\n",
1216 " <td>2.992197e+12</td>\n",
1217 " <td>3.421229e+12</td>\n",
1218 " <td>3.730028e+12</td>\n",
1219 " <td>3.397791e+12</td>\n",
1220 " <td>3.396354e+12</td>\n",
1221 " <td>3.744409e+12</td>\n",
1222 " <td>3.527345e+12</td>\n",
1223 " <td>3.732743e+12</td>\n",
1224 " <td>3.883920e+12</td>\n",
1225 " <td>3.356236e+12</td>\n",
1226 " </tr>\n",
1227 " <tr>\n",
1228 " <th>Russian Federation</th>\n",
1229 " <td>9.899305e+11</td>\n",
1230 " <td>1.299706e+12</td>\n",
1231 " <td>1.660846e+12</td>\n",
1232 " <td>1.222644e+12</td>\n",
1233 " <td>1.524917e+12</td>\n",
1234 " <td>2.045926e+12</td>\n",
1235 " <td>2.208296e+12</td>\n",
1236 " <td>2.292473e+12</td>\n",
1237 " <td>2.059242e+12</td>\n",
1238 " <td>1.363481e+12</td>\n",
1239 " </tr>\n",
1240 " <tr>\n",
1241 " <th>Canada</th>\n",
1242 " <td>1.315415e+12</td>\n",
1243 " <td>1.464977e+12</td>\n",
1244 " <td>1.549131e+12</td>\n",
1245 " <td>1.371153e+12</td>\n",
1246 " <td>1.613464e+12</td>\n",
1247 " <td>1.788648e+12</td>\n",
1248 " <td>1.828689e+12</td>\n",
1249 " <td>1.847209e+12</td>\n",
1250 " <td>1.803533e+12</td>\n",
1251 " <td>1.556130e+12</td>\n",
1252 " </tr>\n",
1253 " <tr>\n",
1254 " <th>Italy</th>\n",
1255 " <td>1.947920e+12</td>\n",
1256 " <td>2.210293e+12</td>\n",
1257 " <td>2.398857e+12</td>\n",
1258 " <td>2.191242e+12</td>\n",
1259 " <td>2.134018e+12</td>\n",
1260 " <td>2.291991e+12</td>\n",
1261 " <td>2.087077e+12</td>\n",
1262 " <td>2.141315e+12</td>\n",
1263 " <td>2.159134e+12</td>\n",
1264 " <td>1.835899e+12</td>\n",
1265 " </tr>\n",
1266 " <tr>\n",
1267 " <th>South Korea</th>\n",
1268 " <td>1.053217e+12</td>\n",
1269 " <td>1.172614e+12</td>\n",
1270 " <td>1.047339e+12</td>\n",
1271 " <td>9.439419e+11</td>\n",
1272 " <td>1.144067e+12</td>\n",
1273 " <td>1.253223e+12</td>\n",
1274 " <td>1.278428e+12</td>\n",
1275 " <td>1.370795e+12</td>\n",
1276 " <td>1.484318e+12</td>\n",
1277 " <td>1.465773e+12</td>\n",
1278 " </tr>\n",
1279 " <tr>\n",
1280 " <th>France</th>\n",
1281 " <td>2.318594e+12</td>\n",
1282 " <td>2.657213e+12</td>\n",
1283 " <td>2.918383e+12</td>\n",
1284 " <td>2.690222e+12</td>\n",
1285 " <td>2.642610e+12</td>\n",
1286 " <td>2.861408e+12</td>\n",
1287 " <td>2.683825e+12</td>\n",
1288 " <td>2.811078e+12</td>\n",
1289 " <td>2.852166e+12</td>\n",
1290 " <td>2.438208e+12</td>\n",
1291 " </tr>\n",
1292 " <tr>\n",
1293 " <th>Iran</th>\n",
1294 " <td>2.662989e+11</td>\n",
1295 " <td>3.498816e+11</td>\n",
1296 " <td>4.123362e+11</td>\n",
1297 " <td>4.163970e+11</td>\n",
1298 " <td>4.868076e+11</td>\n",
1299 " <td>5.807649e+11</td>\n",
1300 " <td>5.988685e+11</td>\n",
1301 " <td>4.602931e+11</td>\n",
1302 " <td>4.326870e+11</td>\n",
1303 " <td>3.849515e+11</td>\n",
1304 " </tr>\n",
1305 " <tr>\n",
1306 " <th>Spain</th>\n",
1307 " <td>1.259344e+12</td>\n",
1308 " <td>1.472131e+12</td>\n",
1309 " <td>1.625225e+12</td>\n",
1310 " <td>1.485583e+12</td>\n",
1311 " <td>1.420722e+12</td>\n",
1312 " <td>1.478773e+12</td>\n",
1313 " <td>1.324820e+12</td>\n",
1314 " <td>1.354757e+12</td>\n",
1315 " <td>1.369399e+12</td>\n",
1316 " <td>1.195119e+12</td>\n",
1317 " </tr>\n",
1318 " <tr>\n",
1319 " <th>Brazil</th>\n",
1320 " <td>1.107640e+12</td>\n",
1321 " <td>1.397084e+12</td>\n",
1322 " <td>1.695825e+12</td>\n",
1323 " <td>1.667020e+12</td>\n",
1324 " <td>2.208872e+12</td>\n",
1325 " <td>2.616201e+12</td>\n",
1326 " <td>2.465189e+12</td>\n",
1327 " <td>2.472807e+12</td>\n",
1328 " <td>2.455994e+12</td>\n",
1329 " <td>1.802214e+12</td>\n",
1330 " </tr>\n",
1331 " <tr>\n",
1332 " <th>Australia</th>\n",
1333 " <td>7.460542e+11</td>\n",
1334 " <td>8.530996e+11</td>\n",
1335 " <td>1.053996e+12</td>\n",
1336 " <td>9.278052e+11</td>\n",
1337 " <td>1.146138e+12</td>\n",
1338 " <td>1.396650e+12</td>\n",
1339 " <td>1.546152e+12</td>\n",
1340 " <td>1.576184e+12</td>\n",
1341 " <td>1.467484e+12</td>\n",
1342 " <td>1.351694e+12</td>\n",
1343 " </tr>\n",
1344 " </tbody>\n",
1345 "</table>\n",
1346 "</div>"
1347 ],
1348 "text/plain": [
1349 " 2006 2007 2008 2009 \\\n",
1350 "Country Name \n",
1351 "China 2.752132e+12 3.550343e+12 4.594307e+12 5.101703e+12 \n",
1352 "United States 1.381461e+13 1.445186e+13 1.471284e+13 1.444893e+13 \n",
1353 "India 9.402599e+11 1.216735e+12 1.198896e+12 1.341887e+12 \n",
1354 "Japan 4.530377e+12 4.515265e+12 5.037908e+12 5.231383e+12 \n",
1355 "United Kingdom 2.713750e+12 3.100882e+12 2.922667e+12 2.410910e+12 \n",
1356 "Germany 2.992197e+12 3.421229e+12 3.730028e+12 3.397791e+12 \n",
1357 "Russian Federation 9.899305e+11 1.299706e+12 1.660846e+12 1.222644e+12 \n",
1358 "Canada 1.315415e+12 1.464977e+12 1.549131e+12 1.371153e+12 \n",
1359 "Italy 1.947920e+12 2.210293e+12 2.398857e+12 2.191242e+12 \n",
1360 "South Korea 1.053217e+12 1.172614e+12 1.047339e+12 9.439419e+11 \n",
1361 "France 2.318594e+12 2.657213e+12 2.918383e+12 2.690222e+12 \n",
1362 "Iran 2.662989e+11 3.498816e+11 4.123362e+11 4.163970e+11 \n",
1363 "Spain 1.259344e+12 1.472131e+12 1.625225e+12 1.485583e+12 \n",
1364 "Brazil 1.107640e+12 1.397084e+12 1.695825e+12 1.667020e+12 \n",
1365 "Australia 7.460542e+11 8.530996e+11 1.053996e+12 9.278052e+11 \n",
1366 "\n",
1367 " 2010 2011 2012 2013 \\\n",
1368 "Country Name \n",
1369 "China 6.087164e+12 7.551500e+12 8.532230e+12 9.570406e+12 \n",
1370 "United States 1.499205e+13 1.554258e+13 1.619701e+13 1.678485e+13 \n",
1371 "India 1.675615e+12 1.823050e+12 1.827638e+12 1.856722e+12 \n",
1372 "Japan 5.700098e+12 6.157460e+12 6.203213e+12 5.155717e+12 \n",
1373 "United Kingdom 2.475244e+12 2.659310e+12 2.704888e+12 2.786023e+12 \n",
1374 "Germany 3.396354e+12 3.744409e+12 3.527345e+12 3.732743e+12 \n",
1375 "Russian Federation 1.524917e+12 2.045926e+12 2.208296e+12 2.292473e+12 \n",
1376 "Canada 1.613464e+12 1.788648e+12 1.828689e+12 1.847209e+12 \n",
1377 "Italy 2.134018e+12 2.291991e+12 2.087077e+12 2.141315e+12 \n",
1378 "South Korea 1.144067e+12 1.253223e+12 1.278428e+12 1.370795e+12 \n",
1379 "France 2.642610e+12 2.861408e+12 2.683825e+12 2.811078e+12 \n",
1380 "Iran 4.868076e+11 5.807649e+11 5.988685e+11 4.602931e+11 \n",
1381 "Spain 1.420722e+12 1.478773e+12 1.324820e+12 1.354757e+12 \n",
1382 "Brazil 2.208872e+12 2.616201e+12 2.465189e+12 2.472807e+12 \n",
1383 "Australia 1.146138e+12 1.396650e+12 1.546152e+12 1.576184e+12 \n",
1384 "\n",
1385 " 2014 2015 \n",
1386 "Country Name \n",
1387 "China 1.047568e+13 1.106155e+13 \n",
1388 "United States 1.752716e+13 1.822470e+13 \n",
1389 "India 2.039127e+12 2.103588e+12 \n",
1390 "Japan 4.850414e+12 4.389476e+12 \n",
1391 "United Kingdom 3.063803e+12 2.928591e+12 \n",
1392 "Germany 3.883920e+12 3.356236e+12 \n",
1393 "Russian Federation 2.059242e+12 1.363481e+12 \n",
1394 "Canada 1.803533e+12 1.556130e+12 \n",
1395 "Italy 2.159134e+12 1.835899e+12 \n",
1396 "South Korea 1.484318e+12 1.465773e+12 \n",
1397 "France 2.852166e+12 2.438208e+12 \n",
1398 "Iran 4.326870e+11 3.849515e+11 \n",
1399 "Spain 1.369399e+12 1.195119e+12 \n",
1400 "Brazil 2.455994e+12 1.802214e+12 \n",
1401 "Australia 1.467484e+12 1.351694e+12 "
1402 ]
1403 },
1404 "execution_count": 19,
1405 "metadata": {},
1406 "output_type": "execute_result"
1407 }
1408 ],
1409 "source": [
1410 "final1.iloc[:,10:]"
1411 ]
1412 },
1413 {
1414 "cell_type": "code",
1415 "execution_count": 20,
1416 "id": "8d1df660",
1417 "metadata": {},
1418 "outputs": [
1419 {
1420 "data": {
1421 "text/html": [
1422 "<div>\n",
1423 "<style scoped>\n",
1424 " .dataframe tbody tr th:only-of-type {\n",
1425 " vertical-align: middle;\n",
1426 " }\n",
1427 "\n",
1428 " .dataframe tbody tr th {\n",
1429 " vertical-align: top;\n",
1430 " }\n",
1431 "\n",
1432 " .dataframe thead th {\n",
1433 " text-align: right;\n",
1434 " }\n",
1435 "</style>\n",
1436 "<table border=\"1\" class=\"dataframe\">\n",
1437 " <thead>\n",
1438 " <tr style=\"text-align: right;\">\n",
1439 " <th></th>\n",
1440 " <th>Country Name</th>\n",
1441 " <th>Energy Supply</th>\n",
1442 " <th>Energy Supply per Capita</th>\n",
1443 " <th>% Renewable</th>\n",
1444 " </tr>\n",
1445 " <tr>\n",
1446 " <th>Country Name</th>\n",
1447 " <th></th>\n",
1448 " <th></th>\n",
1449 " <th></th>\n",
1450 " <th></th>\n",
1451 " </tr>\n",
1452 " </thead>\n",
1453 " <tbody>\n",
1454 " <tr>\n",
1455 " <th>Afghanistan</th>\n",
1456 " <td>Afghanistan</td>\n",
1457 " <td>321000000</td>\n",
1458 " <td>10</td>\n",
1459 " <td>78.669280</td>\n",
1460 " </tr>\n",
1461 " <tr>\n",
1462 " <th>Albania</th>\n",
1463 " <td>Albania</td>\n",
1464 " <td>102000000</td>\n",
1465 " <td>35</td>\n",
1466 " <td>100.000000</td>\n",
1467 " </tr>\n",
1468 " <tr>\n",
1469 " <th>Algeria</th>\n",
1470 " <td>Algeria</td>\n",
1471 " <td>1959000000</td>\n",
1472 " <td>51</td>\n",
1473 " <td>0.551010</td>\n",
1474 " </tr>\n",
1475 " <tr>\n",
1476 " <th>American Samoa</th>\n",
1477 " <td>American Samoa</td>\n",
1478 " <td>.................................................</td>\n",
1479 " <td>...</td>\n",
1480 " <td>0.641026</td>\n",
1481 " </tr>\n",
1482 " <tr>\n",
1483 " <th>Andorra</th>\n",
1484 " <td>Andorra</td>\n",
1485 " <td>9000000</td>\n",
1486 " <td>121</td>\n",
1487 " <td>88.695650</td>\n",
1488 " </tr>\n",
1489 " <tr>\n",
1490 " <th>...</th>\n",
1491 " <td>...</td>\n",
1492 " <td>...</td>\n",
1493 " <td>...</td>\n",
1494 " <td>...</td>\n",
1495 " </tr>\n",
1496 " <tr>\n",
1497 " <th>Viet Nam</th>\n",
1498 " <td>Viet Nam</td>\n",
1499 " <td>2554000000</td>\n",
1500 " <td>28</td>\n",
1501 " <td>45.321520</td>\n",
1502 " </tr>\n",
1503 " <tr>\n",
1504 " <th>Wallis and Futuna Islands</th>\n",
1505 " <td>Wallis and Futuna Islands</td>\n",
1506 " <td>0</td>\n",
1507 " <td>26</td>\n",
1508 " <td>0.000000</td>\n",
1509 " </tr>\n",
1510 " <tr>\n",
1511 " <th>Yemen</th>\n",
1512 " <td>Yemen</td>\n",
1513 " <td>344000000</td>\n",
1514 " <td>13</td>\n",
1515 " <td>0.000000</td>\n",
1516 " </tr>\n",
1517 " <tr>\n",
1518 " <th>Zambia</th>\n",
1519 " <td>Zambia</td>\n",
1520 " <td>400000000</td>\n",
1521 " <td>26</td>\n",
1522 " <td>99.714670</td>\n",
1523 " </tr>\n",
1524 " <tr>\n",
1525 " <th>Zimbabwe</th>\n",
1526 " <td>Zimbabwe</td>\n",
1527 " <td>480000000</td>\n",
1528 " <td>32</td>\n",
1529 " <td>52.536120</td>\n",
1530 " </tr>\n",
1531 " </tbody>\n",
1532 "</table>\n",
1533 "<p>227 rows × 4 columns</p>\n",
1534 "</div>"
1535 ],
1536 "text/plain": [
1537 " Country Name \\\n",
1538 "Country Name \n",
1539 "Afghanistan Afghanistan \n",
1540 "Albania Albania \n",
1541 "Algeria Algeria \n",
1542 "American Samoa American Samoa \n",
1543 "Andorra Andorra \n",
1544 "... ... \n",
1545 "Viet Nam Viet Nam \n",
1546 "Wallis and Futuna Islands Wallis and Futuna Islands \n",
1547 "Yemen Yemen \n",
1548 "Zambia Zambia \n",
1549 "Zimbabwe Zimbabwe \n",
1550 "\n",
1551 " Energy Supply \\\n",
1552 "Country Name \n",
1553 "Afghanistan 321000000 \n",
1554 "Albania 102000000 \n",
1555 "Algeria 1959000000 \n",
1556 "American Samoa ................................................. \n",
1557 "Andorra 9000000 \n",
1558 "... ... \n",
1559 "Viet Nam 2554000000 \n",
1560 "Wallis and Futuna Islands 0 \n",
1561 "Yemen 344000000 \n",
1562 "Zambia 400000000 \n",
1563 "Zimbabwe 480000000 \n",
1564 "\n",
1565 " Energy Supply per Capita % Renewable \n",
1566 "Country Name \n",
1567 "Afghanistan 10 78.669280 \n",
1568 "Albania 35 100.000000 \n",
1569 "Algeria 51 0.551010 \n",
1570 "American Samoa ... 0.641026 \n",
1571 "Andorra 121 88.695650 \n",
1572 "... ... ... \n",
1573 "Viet Nam 28 45.321520 \n",
1574 "Wallis and Futuna Islands 26 0.000000 \n",
1575 "Yemen 13 0.000000 \n",
1576 "Zambia 26 99.714670 \n",
1577 "Zimbabwe 32 52.536120 \n",
1578 "\n",
1579 "[227 rows x 4 columns]"
1580 ]
1581 },
1582 "execution_count": 20,
1583 "metadata": {},
1584 "output_type": "execute_result"
1585 }
1586 ],
1587 "source": [
1588 "ei"
1589 ]
1590 },
1591 {
1592 "cell_type": "code",
1593 "execution_count": 21,
1594 "id": "3d3500cc",
1595 "metadata": {},
1596 "outputs": [],
1597 "source": [
1598 "l=[127191000000.0,90838000000.0,18984000000.0,7920000000.0,30709000000.0,\n",
1599 " 10431000000.0,13261000000.0,33195000000.0,10597000000.0,11007000000.0,\n",
1600 " 6530000000.0,4923000000.0,9172000000.0,5386000000.0,12149000000.0]"
1601 ]
1602 },
1603 {
1604 "cell_type": "code",
1605 "execution_count": 23,
1606 "id": "896f78ed",
1607 "metadata": {},
1608 "outputs": [
1609 {
1610 "data": {
1611 "text/plain": [
1612 "264"
1613 ]
1614 },
1615 "execution_count": 23,
1616 "metadata": {},
1617 "output_type": "execute_result"
1618 }
1619 ],
1620 "source": [
1621 "len(wb)"
1622 ]
1623 },
1624 {
1625 "cell_type": "code",
1626 "execution_count": 28,
1627 "id": "eaed7095",
1628 "metadata": {},
1629 "outputs": [
1630 {
1631 "data": {
1632 "text/plain": [
1633 "208"
1634 ]
1635 },
1636 "execution_count": 28,
1637 "metadata": {},
1638 "output_type": "execute_result"
1639 }
1640 ],
1641 "source": [
1642 "len(sc)"
1643 ]
1644 },
1645 {
1646 "cell_type": "code",
1647 "execution_count": 25,
1648 "id": "0f3bc850",
1649 "metadata": {},
1650 "outputs": [
1651 {
1652 "data": {
1653 "text/plain": [
1654 "227"
1655 ]
1656 },
1657 "execution_count": 25,
1658 "metadata": {},
1659 "output_type": "execute_result"
1660 }
1661 ],
1662 "source": [
1663 "len(ei)"
1664 ]
1665 },
1666 {
1667 "cell_type": "code",
1668 "execution_count": 30,
1669 "id": "0e84bc5e",
1670 "metadata": {},
1671 "outputs": [
1672 {
1673 "data": {
1674 "text/plain": [
1675 "193"
1676 ]
1677 },
1678 "execution_count": 30,
1679 "metadata": {},
1680 "output_type": "execute_result"
1681 }
1682 ],
1683 "source": [
1684 "208-15\n"
1685 ]
1686 },
1687 {
1688 "cell_type": "code",
1689 "execution_count": 29,
1690 "id": "4d5cb0b6",
1691 "metadata": {},
1692 "outputs": [
1693 {
1694 "data": {
1695 "text/plain": [
1696 "249"
1697 ]
1698 },
1699 "execution_count": 29,
1700 "metadata": {},
1701 "output_type": "execute_result"
1702 }
1703 ],
1704 "source": [
1705 "264-15"
1706 ]
1707 },
1708 {
1709 "cell_type": "code",
1710 "execution_count": 31,
1711 "id": "410c1633",
1712 "metadata": {},
1713 "outputs": [
1714 {
1715 "data": {
1716 "text/plain": [
1717 "212"
1718 ]
1719 },
1720 "execution_count": 31,
1721 "metadata": {},
1722 "output_type": "execute_result"
1723 }
1724 ],
1725 "source": [
1726 "227-15"
1727 ]
1728 },
1729 {
1730 "cell_type": "code",
1731 "execution_count": 33,
1732 "id": "37e5aa48",
1733 "metadata": {},
1734 "outputs": [],
1735 "source": [
1736 "import numpy as np"
1737 ]
1738 },
1739 {
1740 "cell_type": "code",
1741 "execution_count": 38,
1742 "id": "5ecd3aef",
1743 "metadata": {},
1744 "outputs": [],
1745 "source": [
1746 "a= np.arange(1,31).reshape((5,6))"
1747 ]
1748 },
1749 {
1750 "cell_type": "code",
1751 "execution_count": 41,
1752 "id": "f33a2b83",
1753 "metadata": {},
1754 "outputs": [
1755 {
1756 "data": {
1757 "text/plain": [
1758 "array([[ 1, 2, 3, 4, 5, 6],\n",
1759 " [ 7, 8, 9, 10, 11, 12],\n",
1760 " [13, 14, 15, 16, 17, 18],\n",
1761 " [19, 20, 21, 22, 23, 24],\n",
1762 " [25, 26, 27, 28, 29, 30]])"
1763 ]
1764 },
1765 "execution_count": 41,
1766 "metadata": {},
1767 "output_type": "execute_result"
1768 }
1769 ],
1770 "source": [
1771 "a"
1772 ]
1773 },
1774 {
1775 "cell_type": "code",
1776 "execution_count": null,
1777 "id": "2cd51e60",
1778 "metadata": {},
1779 "outputs": [],
1780 "source": []
1781 }
1782 ],
1783 "metadata": {
1784 "kernelspec": {
1785 "display_name": "Python 3",
1786 "language": "python",
1787 "name": "python3"
1788 },
1789 "language_info": {
1790 "codemirror_mode": {
1791 "name": "ipython",
1792 "version": 3
1793 },
1794 "file_extension": ".py",
1795 "mimetype": "text/x-python",
1796 "name": "python",
1797 "nbconvert_exporter": "python",
1798 "pygments_lexer": "ipython3",
1799 "version": "3.8.8"
1800 }
1801 },
1802 "nbformat": 4,
1803 "nbformat_minor": 5
1804 }
1805