Fakultas Ilmu Komputer UI

Commit bf41280e authored by Ahmad Dzikrul Fikri's avatar Ahmad Dzikrul Fikri
Browse files

Lab13 - 1806196806

parent f3f578c3
...@@ -1436,12 +1436,12 @@ ...@@ -1436,12 +1436,12 @@
}, },
{ {
"cell_type": "code", "cell_type": "code",
"execution_count": 5, "execution_count": 8,
"metadata": {}, "metadata": {},
"outputs": [ "outputs": [
{ {
"data": { "data": {
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\n",
"text/plain": [ "text/plain": [
"<Figure size 432x288 with 1 Axes>" "<Figure size 432x288 with 1 Axes>"
] ]
...@@ -1454,7 +1454,7 @@ ...@@ -1454,7 +1454,7 @@
], ],
"source": [ "source": [
"plt.hist(customers['nama'], bins= 10, edgecolor='black')\n", "plt.hist(customers['nama'], bins= 10, edgecolor='black')\n",
"plt.title(\"Diagram Jumlah Order\")\n", "plt.title(\"Diagram nama\")\n",
"plt.xlabel(\"Order\")\n", "plt.xlabel(\"Order\")\n",
"plt.ylabel(\"Frekuensi\")\n", "plt.ylabel(\"Frekuensi\")\n",
"plt.show()" "plt.show()"
......
%% Cell type:code id: tags: %% Cell type:code id: tags:
``` python ``` python
import pandas as pd import pandas as pd
customers = pd.read_csv('data_pelanggan.txt', sep=' ', names = ['nama', 'jumlah','harga']) customers = pd.read_csv('data_pelanggan.txt', sep=' ', names = ['nama', 'jumlah','harga'])
pd.set_option('display.max_rows',None) pd.set_option('display.max_rows',None)
print(customers) print(customers)
``` ```
%%%% Output: stream %%%% Output: stream
nama jumlah harga nama jumlah harga
0 LAUREN 497 7952000 0 LAUREN 497 7952000
1 HARRY 496 7936000 1 HARRY 496 7936000
2 YPPOP 495 7920000 2 YPPOP 495 7920000
3 HENRY 494 7904000 3 HENRY 494 7904000
4 ISABELLA 492 7872000 4 ISABELLA 492 7872000
5 NOSAM 489 7824000 5 NOSAM 489 7824000
6 CHARLOTTE 487 7792000 6 CHARLOTTE 487 7792000
7 CAASI 485 7760000 7 CAASI 485 7760000
8 SIENNA 485 7760000 8 SIENNA 485 7760000
9 YLLOH 481 7696000 9 YLLOH 481 7696000
10 BETHANY 480 7680000 10 BETHANY 480 7680000
11 AIRAM 478 7648000 11 AIRAM 478 7648000
12 MORGAN 478 7648000 12 MORGAN 478 7648000
13 LOUIS 477 7632000 13 LOUIS 477 7632000
14 YMA 477 7632000 14 YMA 477 7632000
15 YELIAB 476 7616000 15 YELIAB 476 7616000
16 ISOBEL 476 7616000 16 ISOBEL 476 7616000
17 ADLITAM 474 7584000 17 ADLITAM 474 7584000
18 YECAL 468 7488000 18 YECAL 468 7488000
19 REBMA 466 7456000 19 REBMA 466 7456000
20 ACCEBER 463 7408000 20 ACCEBER 463 7408000
21 NAIK 463 7408000 21 NAIK 463 7408000
22 ALISHA 457 7312000 22 ALISHA 457 7312000
23 AMELIA 456 7296000 23 AMELIA 456 7296000
24 NAGOL 453 7248000 24 NAGOL 453 7248000
25 NATHAN 453 7248000 25 NATHAN 453 7248000
26 FREYA 451 7216000 26 FREYA 451 7216000
27 ELLIOT 498 7171200 27 ELLIOT 498 7171200
28 EVA 497 7156800 28 EVA 497 7156800
29 YLIME 446 7136000 29 YLIME 446 7136000
30 YELIR 445 7120000 30 YELIR 445 7120000
31 YAJ 443 7088000 31 YAJ 443 7088000
32 HARRIET 437 6992000 32 HARRIET 437 6992000
33 YCUL 437 6992000 33 YCUL 437 6992000
34 YLIL 436 6976000 34 YLIL 436 6976000
35 HTEBAZILE 433 6928000 35 HTEBAZILE 433 6928000
36 LUCAS 432 6912000 36 LUCAS 432 6912000
37 LOGAN 432 6912000 37 LOGAN 432 6912000
38 EITAK 477 6868800 38 EITAK 477 6868800
39 IMOGEN 428 6848000 39 IMOGEN 428 6848000
40 LIAM 428 6848000 40 LIAM 428 6848000
41 COREY 428 6848000 41 COREY 428 6848000
42 AMME 426 6816000 42 AMME 426 6816000
43 OWEN 422 6752000 43 OWEN 422 6752000
44 ALICE 419 6704000 44 ALICE 419 6704000
45 BLAKE 418 6688000 45 BLAKE 418 6688000
46 NODNARB 415 6640000 46 NODNARB 415 6640000
47 LIAGIBA 412 6592000 47 LIAGIBA 412 6592000
48 SACUL 410 6560000 48 SACUL 410 6560000
49 EILLOH 455 6552000 49 EILLOH 455 6552000
50 NORAA 406 6496000 50 NORAA 406 6496000
51 EISOR 450 6480000 51 EISOR 450 6480000
52 SEMAJ 405 6480000 52 SEMAJ 405 6480000
53 LIBBY 404 6464000 53 LIBBY 404 6464000
54 REECE 404 6464000 54 REECE 404 6464000
55 ZARA 401 6416000 55 ZARA 401 6416000
56 MOHAMMAD 400 6400000 56 MOHAMMAD 400 6400000
57 NAWE 499 6387200 57 NAWE 499 6387200
58 LEAH 499 6387200 58 LEAH 499 6387200
59 EOZ 442 6364800 59 EOZ 442 6364800
60 RUBY 396 6336000 60 RUBY 396 6336000
61 BOCAJ 394 6304000 61 BOCAJ 394 6304000
62 FINLEY 393 6288000 62 FINLEY 393 6288000
63 HARVEY 393 6288000 63 HARVEY 393 6288000
64 JAKE 392 6272000 64 JAKE 392 6272000
65 MUHAMMAD 392 6272000 65 MUHAMMAD 392 6272000
66 POPPY 392 6272000 66 POPPY 392 6272000
67 YBOT 392 6272000 67 YBOT 392 6272000
68 MOLLY 390 6240000 68 MOLLY 390 6240000
69 RONNOC 390 6240000 69 RONNOC 390 6240000
70 EIMAJ 433 6235200 70 EIMAJ 433 6235200
71 BEN 388 6208000 71 BEN 388 6208000
72 TTELRACS 386 6176000 72 TTELRACS 386 6176000
73 SIWEL 385 6160000 73 SIWEL 385 6160000
74 NOSIDAM 384 6144000 74 NOSIDAM 384 6144000
75 WEHTTAM 383 6128000 75 WEHTTAM 383 6128000
76 SARAH 382 6112000 76 SARAH 382 6112000
77 NOTHSA 381 6096000 77 NOTHSA 381 6096000
78 AIVILO 377 6032000 78 AIVILO 377 6032000
79 ANNA 377 6032000 79 ANNA 377 6032000
80 CAITLIN 376 6016000 80 CAITLIN 376 6016000
81 REUBEN 376 6016000 81 REUBEN 376 6016000
82 YBUR 374 5984000 82 YBUR 374 5984000
83 MARTHA 374 5984000 83 MARTHA 374 5984000
84 AYAM 373 5968000 84 AYAM 373 5968000
85 JASMINE 371 5936000 85 JASMINE 371 5936000
86 EILRAHC 410 5904000 86 EILRAHC 410 5904000
87 KAZ 368 5888000 87 KAZ 368 5888000
88 YALNIF 365 5840000 88 YALNIF 365 5840000
89 EIFLA 500 5760000 89 EIFLA 500 5760000
90 LUCA 360 5760000 90 LUCA 360 5760000
91 SKYE 355 5680000 91 SKYE 355 5680000
92 JOE 352 5632000 92 JOE 352 5632000
93 DAVID 351 5616000 93 DAVID 351 5616000
94 SEBASTIAN 349 5584000 94 SEBASTIAN 349 5584000
95 NEBUER 345 5520000 95 NEBUER 345 5520000
96 YLLIB 344 5504000 96 YLLIB 344 5504000
97 NAGEM 343 5488000 97 NAGEM 343 5488000
98 AIGROEG 341 5456000 98 AIGROEG 341 5456000
99 HTIAF 340 5440000 99 HTIAF 340 5440000
100 DAMMAHOM 340 5440000 100 DAMMAHOM 340 5440000
101 JACK 340 5440000 101 JACK 340 5440000
102 YSIAD 340 5440000 102 YSIAD 340 5440000
103 BRANDON 337 5392000 103 BRANDON 337 5392000
104 LILY 337 5392000 104 LILY 337 5392000
105 ISABEL 335 5360000 105 ISABEL 335 5360000
106 NYLEVE 334 5344000 106 NYLEVE 334 5344000
107 SAMOHT 333 5328000 107 SAMOHT 333 5328000
108 CAMERON 333 5328000 108 CAMERON 333 5328000
109 NICOLE 329 5264000 109 NICOLE 329 5264000
110 NAES 324 5184000 110 NAES 324 5184000
111 AIHPOS 321 5136000 111 AIHPOS 321 5136000
112 JOHN 321 5136000 112 JOHN 321 5136000
113 SOPHIE 320 5120000 113 SOPHIE 320 5120000
114 ALLEBASI 320 5120000 114 ALLEBASI 320 5120000
115 YENTRUOC 318 5088000 115 YENTRUOC 318 5088000
116 LILLY 316 5056000 116 LILLY 316 5056000
117 JOEL 310 4960000 117 JOEL 310 4960000
118 EILLE 341 4910400 118 EILLE 341 4910400
119 TOBY 305 4880000 119 TOBY 305 4880000
120 LEOJ 303 4848000 120 LEOJ 303 4848000
121 MADA 303 4848000 121 MADA 303 4848000
122 ALEX 302 4832000 122 ALEX 302 4832000
123 ECNEROLF 334 4809600 123 ECNEROLF 334 4809600
124 MULLAC 300 4800000 124 MULLAC 300 4800000
125 DAISY 299 4784000 125 DAISY 299 4784000
126 YRRAH 298 4768000 126 YRRAH 298 4768000
127 SAM 298 4768000 127 SAM 298 4768000
128 DYLAN 298 4768000 128 DYLAN 298 4768000
129 ACUL 296 4736000 129 ACUL 296 4736000
130 MILLIE 295 4720000 130 MILLIE 295 4720000
131 NEDYAJ 295 4720000 131 NEDYAJ 295 4720000
132 ALLE 295 4720000 132 ALLE 295 4720000
133 HPESOJ 292 4672000 133 HPESOJ 292 4672000
134 EMILY 324 4665600 134 EMILY 324 4665600
135 NIMAJNEB 291 4656000 135 NIMAJNEB 291 4656000
136 LEBASI 288 4608000 136 LEBASI 288 4608000
137 NAGROM 288 4608000 137 NAGROM 288 4608000
138 JACOB 285 4560000 138 JACOB 285 4560000
139 RILEY 284 4544000 139 RILEY 284 4544000
140 REBECCA 277 4432000 140 REBECCA 277 4432000
141 GRACE 277 4432000 141 GRACE 277 4432000
142 RACSO 273 4368000 142 RACSO 273 4368000
143 NAITSABES 273 4368000 143 NAITSABES 273 4368000
144 LOLA 271 4336000 144 LOLA 271 4336000
145 XAM 268 4288000 145 XAM 268 4288000
146 YBBIL 264 4224000 146 YBBIL 264 4224000
147 NIRE 263 4208000 147 NIRE 263 4208000
148 FAITH 262 4192000 148 FAITH 262 4192000
149 YNAHTEB 262 4192000 149 YNAHTEB 262 4192000
150 NEB 261 4176000 150 NEB 261 4176000
151 BRADLEY 261 4176000 151 BRADLEY 261 4176000
152 LAYLA 261 4176000 152 LAYLA 261 4176000
153 LUKE 258 4128000 153 LUKE 258 4128000
154 JAYDEN 256 4096000 154 JAYDEN 256 4096000
155 YLLIT 253 4048000 155 YLLIT 253 4048000
156 ACSECNARF 253 4048000 156 ACSECNARF 253 4048000
157 SUMMER 252 4032000 157 SUMMER 252 4032000
158 NEDYAH 250 4000000 158 NEDYAH 250 4000000
159 EMILIA 277 3988800 159 EMILIA 277 3988800
160 EKALB 276 3974400 160 EKALB 276 3974400
161 CONNOR 248 3968000 161 CONNOR 248 3968000
162 PHOEBE 248 3968000 162 PHOEBE 248 3968000
163 EYKS 275 3960000 163 EYKS 275 3960000
164 NOSIRRAH 247 3952000 164 NOSIRRAH 247 3952000
165 MAISIE 247 3952000 165 MAISIE 247 3952000
166 SYHR 247 3952000 166 SYHR 247 3952000
167 ELIZABETH 273 3931200 167 ELIZABETH 273 3931200
168 EKUL 273 3931200 168 EKUL 273 3931200
169 OSCAR 245 3920000 169 OSCAR 245 3920000
170 MARIA 244 3904000 170 MARIA 244 3904000
171 NAHTE 244 3904000 171 NAHTE 244 3904000
172 AARON 243 3888000 172 AARON 243 3888000
173 TILLY 241 3856000 173 TILLY 241 3856000
174 NOEL 240 3840000 174 NOEL 240 3840000
175 ELLIS 266 3830400 175 ELLIS 266 3830400
176 ESME 263 3787200 176 ESME 263 3787200
177 OLIVIA 235 3760000 177 OLIVIA 235 3760000
178 EKAJ 256 3686400 178 EKAJ 256 3686400
179 AILUJ 228 3648000 179 AILUJ 228 3648000
180 DRAWDE 225 3600000 180 DRAWDE 225 3600000
181 BENJAMIN 223 3568000 181 BENJAMIN 223 3568000
182 WILLIAM 220 3520000 182 WILLIAM 220 3520000
183 ROLYAT 219 3504000 183 ROLYAT 219 3504000
184 LYDIA 218 3488000 184 LYDIA 218 3488000
185 ALEXANDRA 216 3456000 185 ALEXANDRA 216 3456000
186 ACISSEJ 215 3440000 186 ACISSEJ 215 3440000
187 FRANCESCA 215 3440000 187 FRANCESCA 215 3440000
188 EBEOHP 237 3412800 188 EBEOHP 237 3412800
189 ROBERT 212 3392000 189 ROBERT 212 3392000
190 ECILA 232 3340800 190 ECILA 232 3340800
191 EIDDERF 231 3326400 191 EIDDERF 231 3326400
192 JESSICA 207 3312000 192 JESSICA 207 3312000
193 NIAMH 205 3280000 193 NIAMH 205 3280000
194 EDWARD 227 3268800 194 EDWARD 227 3268800
195 ZACHARY 194 3104000 195 ZACHARY 194 3104000
196 ARAZ 193 3088000 196 ARAZ 193 3088000
197 ZOE 193 3088000 197 ZOE 193 3088000
198 HAYDEN 189 3024000 198 HAYDEN 189 3024000
199 SILLE 187 2992000 199 SILLE 187 2992000
200 EIHPOS 207 2980800 200 EIHPOS 207 2980800
201 EGROEG 200 2880000 201 EGROEG 200 2880000
202 ARIEK 178 2848000 202 ARIEK 178 2848000
203 YEROC 177 2832000 203 YEROC 177 2832000
204 BILLY 176 2816000 204 BILLY 176 2816000
205 NOSIDDAM 174 2784000 205 NOSIDDAM 174 2784000
206 NAREIK 174 2784000 206 NAREIK 174 2784000
207 MICHAEL 172 2752000 207 MICHAEL 172 2752000
208 EGIAP 191 2750400 208 EGIAP 191 2750400
209 MAILLIW 171 2736000 209 MAILLIW 171 2736000
210 JULIA 170 2720000 210 JULIA 170 2720000
211 MAYA 169 2704000 211 MAYA 169 2704000
212 HOLLY 168 2688000 212 HOLLY 168 2688000
213 IXEL 168 2688000 213 IXEL 168 2688000
214 OEL 167 2672000 214 OEL 167 2672000
215 AMBER 165 2640000 215 AMBER 165 2640000
216 MATILDA 163 2608000 216 MATILDA 163 2608000
217 AHSILA 163 2608000 217 AHSILA 163 2608000
218 LEXIE 162 2592000 218 LEXIE 162 2592000
219 XELA 160 2560000 219 XELA 160 2560000
220 TIA 157 2512000 220 TIA 157 2512000
221 ECARG 174 2505600 221 ECARG 174 2505600
222 JAY 155 2480000 222 JAY 155 2480000
223 ADAM 152 2432000 223 ADAM 152 2432000
224 GRACIE 150 2400000 224 GRACIE 150 2400000
225 DANIEL 149 2384000 225 DANIEL 149 2384000
226 ELYK 164 2361600 226 ELYK 164 2361600
227 AIT 147 2352000 227 AIT 147 2352000
228 JAMES 147 2352000 228 JAMES 147 2352000
229 EMSE 160 2304000 229 EMSE 160 2304000
230 TAYLOR 142 2272000 230 TAYLOR 142 2272000
231 KAI 141 2256000 231 KAI 141 2256000
232 ETHAN 155 2232000 232 ETHAN 155 2232000
233 FREDDIE 139 2224000 233 FREDDIE 139 2224000
234 AHTRAM 139 2224000 234 AHTRAM 139 2224000
235 EIBBA 152 2188800 235 EIBBA 152 2188800
236 MOHAMMED 133 2128000 236 MOHAMMED 133 2128000
237 THOMAS 132 2112000 237 THOMAS 132 2112000
238 ELEANOR 142 2044800 238 ELEANOR 142 2044800
239 RYAN 125 2000000 239 RYAN 125 2000000
240 COURTNEY 124 1984000 240 COURTNEY 124 1984000
241 EVIE 137 1972800 241 EVIE 137 1972800
242 TOILLE 122 1952000 242 TOILLE 122 1952000
243 AUHSOJ 120 1920000 243 AUHSOJ 120 1920000
244 LEBOSI 119 1904000 244 LEBOSI 119 1904000
245 ALSI 117 1872000 245 ALSI 117 1872000
246 FLORENCE 116 1856000 246 FLORENCE 116 1856000
247 ALICIA 113 1808000 247 ALICIA 113 1808000
248 EVE 123 1771200 248 EVE 123 1771200
249 KIAN 110 1760000 249 KIAN 110 1760000
250 NILTIAC 109 1744000 250 NILTIAC 109 1744000
251 MAX 107 1712000 251 MAX 107 1712000
252 YRAHCAZ 107 1712000 252 YRAHCAZ 107 1712000
253 NAVE 103 1648000 253 NAVE 103 1648000
254 CHARLIE 101 1616000 254 CHARLIE 101 1616000
%% Cell type:markdown id: tags: %% Cell type:markdown id: tags:
diatas adalah Soal 1 diatas adalah Soal 1
%% Cell type:code id: tags: %% Cell type:code id: tags:
``` python ``` python
kolom_pilihan = ['nama', 'jumlah'] kolom_pilihan = ['nama', 'jumlah']
print(customers.loc[10:20,kolom_pilihan]) #menampilkan beberapa kolom dan baris tabel print(customers.loc[10:20,kolom_pilihan]) #menampilkan beberapa kolom dan baris tabel
``` ```
%%%% Output: stream %%%% Output: stream
nama jumlah nama jumlah
10 BETHANY 480 10 BETHANY 480
11 AIRAM 478 11 AIRAM 478
12 MORGAN 478 12 MORGAN 478
13 LOUIS 477 13 LOUIS 477
14 YMA 477 14 YMA 477
15 YELIAB 476 15 YELIAB 476
16 ISOBEL 476 16 ISOBEL 476
17 ADLITAM 474 17 ADLITAM 474
18 YECAL 468 18 YECAL 468
19 REBMA 466 19 REBMA 466
20 ACCEBER 463 20 ACCEBER 463
%% Cell type:code id: tags: %% Cell type:code id: tags:
``` python ``` python
kolom_pilihan = ['nama', 'jumlah'] kolom_pilihan = ['nama', 'jumlah']
print(customers.loc[:,kolom_pilihan]) #menampilkan beberapa kolom tabel dan seluruh baris dengan indexer loc print(customers.loc[:,kolom_pilihan]) #menampilkan beberapa kolom tabel dan seluruh baris dengan indexer loc
``` ```
%%%% Output: stream %%%% Output: stream
nama jumlah nama jumlah
0 LAUREN 497 0 LAUREN 497
1 HARRY 496 1 HARRY 496
2 YPPOP 495 2 YPPOP 495
3 HENRY 494 3 HENRY 494
4 ISABELLA 492 4 ISABELLA 492
5 NOSAM 489 5 NOSAM 489
6 CHARLOTTE 487 6 CHARLOTTE 487
7 CAASI 485 7 CAASI 485
8 SIENNA 485 8 SIENNA 485
9 YLLOH 481 9 YLLOH 481
10 BETHANY 480 10 BETHANY 480
11 AIRAM 478 11 AIRAM 478
12 MORGAN 478 12 MORGAN 478
13 LOUIS 477 13 LOUIS 477
14 YMA 477 14 YMA 477
15 YELIAB 476 15 YELIAB 476
16 ISOBEL 476 16 ISOBEL 476
17 ADLITAM 474 17 ADLITAM 474
18 YECAL 468 18 YECAL 468
19 REBMA 466 19 REBMA 466
20 ACCEBER 463 20 ACCEBER 463
21 NAIK 463 21 NAIK 463
22 ALISHA 457 22 ALISHA 457
23 AMELIA 456 23 AMELIA 456
24 NAGOL 453 24 NAGOL 453
25 NATHAN 453 25 NATHAN 453
26 FREYA 451 26 FREYA 451
27 ELLIOT 498 27 ELLIOT 498
28 EVA 497 28 EVA 497
29 YLIME 446 29 YLIME 446
30 YELIR 445 30 YELIR 445
31 YAJ 443 31 YAJ 443
32 HARRIET 437 32 HARRIET 437
33 YCUL 437 33 YCUL 437
34 YLIL 436 34 YLIL 436
35 HTEBAZILE 433 35 HTEBAZILE 433
36 LUCAS 432 36 LUCAS 432
37 LOGAN 432 37 LOGAN 432
38 EITAK 477 38 EITAK 477
39 IMOGEN 428 39 IMOGEN 428
40 LIAM 428 40 LIAM 428
41 COREY 428 41 COREY 428
42 AMME 426 42 AMME 426
43 OWEN 422 43 OWEN 422
44 ALICE 419 44 ALICE 419
45 BLAKE 418 45 BLAKE 418
46 NODNARB 415 46 NODNARB 415
47 LIAGIBA 412 47 LIAGIBA 412
48 SACUL 410 48 SACUL 410
49 EILLOH 455 49 EILLOH 455
50 NORAA 406 50 NORAA 406
51 EISOR 450 51 EISOR 450
52 SEMAJ 405 52 SEMAJ 405
53 LIBBY 404 53 LIBBY 404
54 REECE 404 54 REECE 404
55 ZARA 401 55 ZARA 401
56 MOHAMMAD 400 56 MOHAMMAD 400
57 NAWE 499 57 NAWE 499
58 LEAH 499 58 LEAH 499
59 EOZ 442 59 EOZ 442
60 RUBY 396 60 RUBY 396
61 BOCAJ 394 61 BOCAJ 394
62 FINLEY 393 62 FINLEY 393
63 HARVEY 393 63 HARVEY 393
64 JAKE 392 64 JAKE 392
65 MUHAMMAD 392 65 MUHAMMAD 392
66 POPPY 392 66 POPPY 392
67 YBOT 392 67 YBOT 392
68 MOLLY 390 68 MOLLY 390
69 RONNOC 390 69 RONNOC 390
70 EIMAJ 433 70 EIMAJ 433
71 BEN 388 71 BEN 388
72 TTELRACS 386 72 TTELRACS 386
73 SIWEL 385 73 SIWEL 385
74 NOSIDAM 384 74 NOSIDAM 384
75 WEHTTAM 383 75 WEHTTAM 383
76 SARAH 382 76 SARAH 382
77 NOTHSA 381 77 NOTHSA 381
78 AIVILO 377 78 AIVILO 377
79 ANNA 377 79 ANNA 377
80 CAITLIN 376 80 CAITLIN 376
81 REUBEN 376 81 REUBEN 376
82 YBUR 374 82 YBUR 374
83 MARTHA 374 83 MARTHA 374
84 AYAM 373 84 AYAM 373
85 JASMINE 371 85 JASMINE 371
86 EILRAHC 410 86 EILRAHC 410
87 KAZ 368 87 KAZ 368
88 YALNIF 365 88 YALNIF 365
89 EIFLA 500 89 EIFLA 500
90 LUCA 360 90 LUCA 360
91 SKYE 355 91 SKYE 355
92 JOE 352 92 JOE 352
93 DAVID 351 93 DAVID 351
94 SEBASTIAN 349 94 SEBASTIAN 349
95 NEBUER 345 95 NEBUER 345
96 YLLIB 344 96 YLLIB 344
97 NAGEM 343 97 NAGEM 343
98 AIGROEG 341 98 AIGROEG 341
99 HTIAF 340 99 HTIAF 340
100 DAMMAHOM 340 100 DAMMAHOM 340
101 JACK 340 101 JACK 340
102 YSIAD 340 102 YSIAD 340
103 BRANDON 337 103 BRANDON 337
104 LILY 337 104 LILY 337
105 ISABEL 335 105 ISABEL 335
106 NYLEVE 334 106 NYLEVE 334
107 SAMOHT 333 107 SAMOHT 333
108 CAMERON 333 108 CAMERON 333
109 NICOLE 329 109 NICOLE 329
110 NAES 324 110 NAES 324
111 AIHPOS 321 111 AIHPOS 321
112 JOHN 321 112 JOHN 321
113 SOPHIE 320 113 SOPHIE 320
114 ALLEBASI 320 114 ALLEBASI 320
115 YENTRUOC 318 115 YENTRUOC 318
116 LILLY 316 116 LILLY 316
117 JOEL 310 117 JOEL 310
118 EILLE 341 118 EILLE 341
119 TOBY 305 119 TOBY 305
120 LEOJ 303 120 LEOJ 303
121 MADA 303 121 MADA 303
122 ALEX 302 122 ALEX 302
123 ECNEROLF 334 123 ECNEROLF 334
124 MULLAC 300 124 MULLAC 300
125 DAISY 299 125 DAISY 299
126 YRRAH 298 126 YRRAH 298
127 SAM 298 127 SAM 298
128 DYLAN 298 128 DYLAN 298
129 ACUL 296 129 ACUL 296
130 MILLIE 295 130 MILLIE 295
131 NEDYAJ 295 131 NEDYAJ 295
132 ALLE 295 132 ALLE 295
133 HPESOJ 292 133 HPESOJ 292
134 EMILY 324 134 EMILY 324
135 NIMAJNEB 291 135 NIMAJNEB 291
136 LEBASI 288 136 LEBASI 288
137 NAGROM 288 137 NAGROM 288
138 JACOB 285 138 JACOB 285
139 RILEY 284 139 RILEY 284
140 REBECCA 277 140 REBECCA 277
141 GRACE 277 141 GRACE 277
142 RACSO 273 142 RACSO 273
143 NAITSABES 273 143 NAITSABES 273
144 LOLA 271 144 LOLA 271
145 XAM 268 145 XAM 268
146 YBBIL 264 146 YBBIL 264
147 NIRE 263 147 NIRE 263
148 FAITH 262 148 FAITH 262
149 YNAHTEB 262 149 YNAHTEB 262
150 NEB 261 150 NEB 261
151 BRADLEY 261 151 BRADLEY 261
152 LAYLA 261 152 LAYLA 261
153 LUKE 258 153 LUKE 258
154 JAYDEN 256 154 JAYDEN 256
155 YLLIT 253 155 YLLIT 253
156 ACSECNARF 253 156 ACSECNARF 253
157 SUMMER 252 157 SUMMER 252
158 NEDYAH 250 158 NEDYAH 250
159 EMILIA 277 159 EMILIA 277
160 EKALB 276 160 EKALB 276
161 CONNOR 248 161 CONNOR 248
162 PHOEBE 248 162 PHOEBE 248
163 EYKS 275 163 EYKS 275
164 NOSIRRAH 247 164 NOSIRRAH 247
165 MAISIE 247 165 MAISIE 247
166 SYHR 247 166 SYHR 247
167 ELIZABETH 273 167 ELIZABETH 273
168 EKUL 273 168 EKUL 273
169 OSCAR 245 169 OSCAR 245
170 MARIA 244 170 MARIA 244
171 NAHTE 244 171 NAHTE 244
172 AARON 243 172 AARON 243
173 TILLY 241 173 TILLY 241
174 NOEL 240 174 NOEL 240
175 ELLIS 266 175 ELLIS 266
176 ESME 263 176 ESME 263
177 OLIVIA 235 177 OLIVIA 235
178 EKAJ 256 178 EKAJ 256
179 AILUJ 228 179 AILUJ 228
180 DRAWDE 225 180 DRAWDE 225
181 BENJAMIN 223 181 BENJAMIN 223
182 WILLIAM 220 182 WILLIAM 220
183 ROLYAT 219 183 ROLYAT 219
184 LYDIA 218 184 LYDIA 218
185 ALEXANDRA 216 185 ALEXANDRA 216
186 ACISSEJ 215 186 ACISSEJ 215
187 FRANCESCA 215 187 FRANCESCA 215
188 EBEOHP 237 188 EBEOHP 237
189 ROBERT 212 189 ROBERT 212
190 ECILA 232 190 ECILA 232
191 EIDDERF 231 191 EIDDERF 231
192 JESSICA 207 192 JESSICA 207
193 NIAMH 205 193 NIAMH 205
194 EDWARD 227 194 EDWARD 227
195 ZACHARY 194 195 ZACHARY 194
196 ARAZ 193 196 ARAZ 193
197 ZOE 193 197 ZOE 193
198 HAYDEN 189 198 HAYDEN 189
199 SILLE 187 199 SILLE 187
200 EIHPOS 207 200 EIHPOS 207
201 EGROEG 200 201 EGROEG 200
202 ARIEK 178 202 ARIEK 178
203 YEROC 177 203 YEROC 177
204 BILLY 176 204 BILLY 176
205 NOSIDDAM 174 205 NOSIDDAM 174
206 NAREIK 174 206 NAREIK 174
207 MICHAEL 172 207 MICHAEL 172
208 EGIAP 191 208 EGIAP 191
209 MAILLIW 171 209 MAILLIW 171
210 JULIA 170 210 JULIA 170
211 MAYA 169 211 MAYA 169
212 HOLLY 168 212 HOLLY 168
213 IXEL 168 213 IXEL 168
214 OEL 167 214 OEL 167
215 AMBER 165 215 AMBER 165
216 MATILDA 163 216 MATILDA 163
217 AHSILA 163 217 AHSILA 163
218 LEXIE 162 218 LEXIE 162
219 XELA 160 219 XELA 160
220 TIA 157 220 TIA 157
221 ECARG 174 221 ECARG 174
222 JAY 155 222 JAY 155
223 ADAM 152 223 ADAM 152
224 GRACIE 150 224 GRACIE 150
225 DANIEL 149 225 DANIEL 149
226 ELYK 164 226 ELYK 164
227 AIT 147 227 AIT 147
228 JAMES 147 228 JAMES 147
229 EMSE 160 229 EMSE 160
230 TAYLOR 142 230 TAYLOR 142
231 KAI 141 231 KAI 141
232 ETHAN 155 232 ETHAN 155
233 FREDDIE 139 233 FREDDIE 139
234 AHTRAM 139 234 AHTRAM 139
235 EIBBA 152 235 EIBBA 152
236 MOHAMMED 133 236 MOHAMMED 133
237 THOMAS 132 237 THOMAS 132
238 ELEANOR 142 238 ELEANOR 142
239 RYAN 125 239 RYAN 125
240 COURTNEY 124 240 COURTNEY 124
241 EVIE 137 241 EVIE 137
242 TOILLE 122 242 TOILLE 122
243 AUHSOJ 120 243 AUHSOJ 120
244 LEBOSI 119 244 LEBOSI 119
245 ALSI 117 245 ALSI 117
246 FLORENCE 116 246 FLORENCE 116
247 ALICIA 113 247 ALICIA 113
248 EVE 123 248 EVE 123
249 KIAN 110 249 KIAN 110
250 NILTIAC 109 250 NILTIAC 109
251 MAX 107 251 MAX 107
252 YRAHCAZ 107 252 YRAHCAZ 107
253 NAVE 103 253 NAVE 103
254 CHARLIE 101 254 CHARLIE 101
%% Cell type:code id: tags: %% Cell type:code id: tags:
``` python ``` python
kondisi1 = customers['jumlah'] > 400 kondisi1 = customers['jumlah'] > 400
kondisi2 = customers['nama'].str.startswith('H') kondisi2 = customers['nama'].str.startswith('H')
kondisi = kondisi1 & kondisi2 kondisi = kondisi1 & kondisi2
print(customers[kondisi]) print(customers[kondisi])
``` ```
%%%% Output: stream %%%% Output: stream
nama jumlah harga nama jumlah harga
1 HARRY 496 7936000 1 HARRY 496 7936000
3 HENRY 494 7904000 3 HENRY 494 7904000
32 HARRIET 437 6992000 32 HARRIET 437 6992000
35 HTEBAZILE 433 6928000 35 HTEBAZILE 433 6928000
%% Cell type:code id: tags: %% Cell type:code id: tags:
``` python ``` python
batas = int(input('masukan batas pemesanan yang ingin ditampilkan :')) batas = int(input('masukan batas pemesanan yang ingin ditampilkan :'))
inisial = input('masukkan inisial dari pemesan :').upper() inisial = input('masukkan inisial dari pemesan :').upper()
kondisi1 = customers['jumlah'] > batas kondisi1 = customers['jumlah'] > batas
kondisi2 = customers['nama'].str.startswith(inisial) kondisi2 = customers['nama'].str.startswith(inisial)
kondisi = kondisi1 & kondisi2 kondisi = kondisi1 & kondisi2
print(customers[kondisi]) print(customers[kondisi])
``` ```
%%%% Output: stream %%%% Output: stream
nama jumlah harga nama jumlah harga
1 HARRY 496 7936000 1 HARRY 496 7936000
3 HENRY 494 7904000 3 HENRY 494 7904000
32 HARRIET 437 6992000 32 HARRIET 437 6992000
35 HTEBAZILE 433 6928000 35 HTEBAZILE 433 6928000
%% Cell type:code id: tags: %% Cell type:code id: tags:
``` python ``` python
batas = int(input('masukan batas pemesanan yang ingin ditampilkan :')) batas = int(input('masukan batas pemesanan yang ingin ditampilkan :'))
inisial = input('masukkan inisial dari pemesan :').upper() inisial = input('masukkan inisial dari pemesan :').upper()
kondisi1 = customers['jumlah'] > batas kondisi1 = customers['jumlah'] > batas
kondisi2 = customers['nama'].str.startswith(inisial) kondisi2 = customers['nama'].str.startswith(inisial)
kondisi = kondisi1 | kondisi2 kondisi = kondisi1 | kondisi2
print(customers[kondisi]) #hasil yang didapat jika menggunakan kondisi1 | kondisi2 adalah gabungan dari dua kondisi tersebut print(customers[kondisi]) #hasil yang didapat jika menggunakan kondisi1 | kondisi2 adalah gabungan dari dua kondisi tersebut
``` ```
%%%% Output: stream %%%% Output: stream
nama jumlah harga nama jumlah harga
0 LAUREN 497 7952000 0 LAUREN 497 7952000
1 HARRY 496 7936000 1 HARRY 496 7936000
2 YPPOP 495 7920000 2 YPPOP 495 7920000
3 HENRY 494 7904000 3 HENRY 494 7904000
4 ISABELLA 492 7872000 4 ISABELLA 492 7872000
5 NOSAM 489 7824000 5 NOSAM 489 7824000
6 CHARLOTTE 487 7792000 6 CHARLOTTE 487 7792000
7 CAASI 485 7760000 7 CAASI 485 7760000
8 SIENNA 485 7760000 8 SIENNA 485 7760000
9 YLLOH 481 7696000 9 YLLOH 481 7696000
10 BETHANY 480 7680000 10 BETHANY 480 7680000
11 AIRAM 478 7648000 11 AIRAM 478 7648000
12 MORGAN 478 7648000 12 MORGAN 478 7648000
13 LOUIS 477 7632000 13 LOUIS 477 7632000
14 YMA 477 7632000 14 YMA 477 7632000
15 YELIAB 476 7616000 15 YELIAB 476 7616000
16 ISOBEL 476 7616000 16 ISOBEL 476 7616000
17 ADLITAM 474 7584000 17 ADLITAM 474 7584000
18 YECAL 468 7488000 18 YECAL 468 7488000
19 REBMA 466 7456000 19 REBMA 466 7456000
20 ACCEBER 463 7408000 20 ACCEBER 463 7408000
21 NAIK 463 7408000 21 NAIK 463 7408000
22 ALISHA 457 7312000 22 ALISHA 457 7312000
23 AMELIA 456 7296000 23 AMELIA 456 7296000
24 NAGOL 453 7248000 24 NAGOL 453 7248000
25 NATHAN 453 7248000 25 NATHAN 453 7248000
26 FREYA 451 7216000 26 FREYA 451 7216000
27 ELLIOT 498 7171200 27 ELLIOT 498 7171200
28 EVA 497 7156800 28 EVA 497 7156800
29 YLIME 446 7136000 29 YLIME 446 7136000
30 YELIR 445 7120000 30 YELIR 445 7120000
31 YAJ 443 7088000 31 YAJ 443 7088000
32 HARRIET 437 6992000 32 HARRIET 437 6992000
33 YCUL 437 6992000 33 YCUL 437 6992000
34 YLIL 436 6976000 34 YLIL 436 6976000
35 HTEBAZILE 433 6928000 35 HTEBAZILE 433 6928000
36 LUCAS 432 6912000 36 LUCAS 432 6912000
37 LOGAN 432 6912000 37 LOGAN 432 6912000
38 EITAK 477 6868800 38 EITAK 477 6868800
39 IMOGEN 428 6848000 39 IMOGEN 428 6848000
40 LIAM 428 6848000 40 LIAM 428 6848000
41 COREY 428 6848000 41 COREY 428 6848000
42 AMME 426 6816000 42 AMME 426 6816000
43 OWEN 422 6752000 43 OWEN 422 6752000
44 ALICE 419 6704000 44 ALICE 419 6704000
45 BLAKE 418 6688000 45 BLAKE 418 6688000
46 NODNARB 415 6640000 46 NODNARB 415 6640000
47 LIAGIBA 412 6592000 47 LIAGIBA 412 6592000
48 SACUL 410 6560000 48 SACUL 410 6560000
49 EILLOH 455 6552000 49 EILLOH 455 6552000
50 NORAA 406 6496000 50 NORAA 406 6496000
51 EISOR 450 6480000 51 EISOR 450 6480000
52 SEMAJ 405 6480000 52 SEMAJ 405 6480000
53 LIBBY 404 6464000 53 LIBBY 404 6464000
54 REECE 404 6464000 54 REECE 404 6464000
55 ZARA 401 6416000 55 ZARA 401 6416000
57 NAWE 499 6387200 57 NAWE 499 6387200
58 LEAH 499 6387200 58 LEAH 499 6387200
59 EOZ 442 6364800 59 EOZ 442 6364800
63 HARVEY 393 6288000 63 HARVEY 393 6288000
70 EIMAJ 433 6235200 70 EIMAJ 433 6235200
86 EILRAHC 410 5904000 86 EILRAHC 410 5904000
89 EIFLA 500 5760000 89 EIFLA 500 5760000
99 HTIAF 340 5440000 99 HTIAF 340 5440000
133 HPESOJ 292 4672000 133 HPESOJ 292 4672000
198 HAYDEN 189 3024000 198 HAYDEN 189 3024000
212 HOLLY 168 2688000 212 HOLLY 168 2688000
%% Cell type:markdown id: tags: %% Cell type:markdown id: tags:
hasil yang didapat jika menggunakan kondisi1 | kondisi2 adalah gabungan dari dua kondisi tersebut hasil yang didapat jika menggunakan kondisi1 | kondisi2 adalah gabungan dari dua kondisi tersebut
%% Cell type:code id: tags: %% Cell type:code id: tags:
``` python ``` python
kondisi1 = customers['harga'] > 6000000 kondisi1 = customers['harga'] > 6000000
print(customers[kondisi1]) print(customers[kondisi1])
``` ```
%%%% Output: stream %%%% Output: stream
nama jumlah harga nama jumlah harga
0 LAUREN 497 7952000 0 LAUREN 497 7952000
1 HARRY 496 7936000 1 HARRY 496 7936000
2 YPPOP 495 7920000 2 YPPOP 495 7920000
3 HENRY 494 7904000 3 HENRY 494 7904000
4 ISABELLA 492 7872000 4 ISABELLA 492 7872000
5 NOSAM 489 7824000 5 NOSAM 489 7824000
6 CHARLOTTE 487 7792000 6 CHARLOTTE 487 7792000
7 CAASI 485 7760000 7 CAASI 485 7760000
8 SIENNA 485 7760000 8 SIENNA 485 7760000
9 YLLOH 481 7696000 9 YLLOH 481 7696000
10 BETHANY 480 7680000 10 BETHANY 480 7680000
11 AIRAM 478 7648000 11 AIRAM 478 7648000
12 MORGAN 478 7648000 12 MORGAN 478 7648000
13 LOUIS 477 7632000 13 LOUIS 477 7632000
14 YMA 477 7632000 14 YMA 477 7632000
15 YELIAB 476 7616000 15 YELIAB 476 7616000
16 ISOBEL 476 7616000 16 ISOBEL 476 7616000
17 ADLITAM 474 7584000 17 ADLITAM 474 7584000
18 YECAL 468 7488000 18 YECAL 468 7488000
19 REBMA 466 7456000 19 REBMA 466 7456000
20 ACCEBER 463 7408000 20 ACCEBER 463 7408000
21 NAIK 463 7408000 21 NAIK 463 7408000
22 ALISHA 457 7312000 22 ALISHA 457 7312000
23 AMELIA 456 7296000 23 AMELIA 456 7296000
24 NAGOL 453 7248000 24 NAGOL 453 7248000
25 NATHAN 453 7248000 25 NATHAN 453 7248000
26 FREYA 451 7216000 26 FREYA 451 7216000
27 ELLIOT 498 7171200 27 ELLIOT 498 7171200
28 EVA 497 7156800 28 EVA 497 7156800
29 YLIME 446 7136000 29 YLIME 446 7136000
30 YELIR 445 7120000 30 YELIR 445 7120000
31 YAJ 443 7088000 31 YAJ 443 7088000
32 HARRIET 437 6992000 32 HARRIET 437 6992000
33 YCUL 437 6992000 33 YCUL 437 6992000
34 YLIL 436 6976000 34 YLIL 436 6976000
35 HTEBAZILE 433 6928000 35 HTEBAZILE 433 6928000
36 LUCAS 432 6912000 36 LUCAS 432 6912000
37 LOGAN 432 6912000 37 LOGAN 432 6912000
38 EITAK 477 6868800 38 EITAK 477 6868800
39 IMOGEN 428 6848000 39 IMOGEN 428 6848000
40 LIAM 428 6848000 40 LIAM 428 6848000
41 COREY 428 6848000 41 COREY 428 6848000
42 AMME 426 6816000 42 AMME 426 6816000
43 OWEN 422 6752000 43 OWEN 422 6752000
44 ALICE 419 6704000 44 ALICE 419 6704000
45 BLAKE 418 6688000 45 BLAKE 418 6688000
46 NODNARB 415 6640000 46 NODNARB 415 6640000
47 LIAGIBA 412 6592000 47 LIAGIBA 412 6592000
48 SACUL 410 6560000 48 SACUL 410 6560000
49 EILLOH 455 6552000 49 EILLOH 455 6552000
50 NORAA 406 6496000 50 NORAA 406 6496000
51 EISOR 450 6480000 51 EISOR 450 6480000
52 SEMAJ 405 6480000 52 SEMAJ 405 6480000
53 LIBBY 404 6464000 53 LIBBY 404 6464000
54 REECE 404 6464000 54 REECE 404 6464000
55 ZARA 401 6416000 55 ZARA 401 6416000
56 MOHAMMAD 400 6400000 56 MOHAMMAD 400 6400000
57 NAWE 499 6387200 57 NAWE 499 6387200
58 LEAH 499 6387200 58 LEAH 499 6387200
59 EOZ 442 6364800 59 EOZ 442 6364800
60 RUBY 396 6336000 60 RUBY 396 6336000
61 BOCAJ 394 6304000 61 BOCAJ 394 6304000
62 FINLEY 393 6288000 62 FINLEY 393 6288000
63 HARVEY 393 6288000 63 HARVEY 393 6288000
64 JAKE 392 6272000 64 JAKE 392 6272000
65 MUHAMMAD 392 6272000 65 MUHAMMAD 392 6272000
66 POPPY 392 6272000 66 POPPY 392 6272000
67 YBOT 392 6272000 67 YBOT 392 6272000
68 MOLLY 390 6240000 68 MOLLY 390 6240000
69 RONNOC 390 6240000 69 RONNOC 390 6240000
70 EIMAJ 433 6235200 70 EIMAJ 433 6235200
71 BEN 388 6208000 71 BEN 388 6208000
72 TTELRACS 386 6176000 72 TTELRACS 386 6176000
73 SIWEL 385 6160000 73 SIWEL 385 6160000
74 NOSIDAM 384 6144000 74 NOSIDAM 384 6144000
75 WEHTTAM 383 6128000 75 WEHTTAM 383 6128000
76 SARAH 382 6112000 76 SARAH 382 6112000
77 NOTHSA 381 6096000 77 NOTHSA 381 6096000
78 AIVILO 377 6032000 78 AIVILO 377 6032000
79 ANNA 377 6032000 79 ANNA 377 6032000
80 CAITLIN 376 6016000 80 CAITLIN 376 6016000
81 REUBEN 376 6016000 81 REUBEN 376 6016000
%% Cell type:code id: tags: %% Cell type:code id: tags:
``` python ``` python
print(customers.sort_values(['nama','jumlah','harga'])) print(customers.sort_values(['nama','jumlah','harga']))
``` ```
%%%% Output: stream %%%% Output: stream
nama jumlah harga nama jumlah harga
172 AARON 243 3888000 172 AARON 243 3888000
20 ACCEBER 463 7408000 20 ACCEBER 463 7408000
186 ACISSEJ 215 3440000 186 ACISSEJ 215 3440000
156 ACSECNARF 253 4048000 156 ACSECNARF 253 4048000
129 ACUL 296 4736000 129 ACUL 296 4736000
223 ADAM 152 2432000 223 ADAM 152 2432000
17 ADLITAM 474 7584000 17 ADLITAM 474 7584000
217 AHSILA 163 2608000 217 AHSILA 163 2608000
234 AHTRAM 139 2224000 234 AHTRAM 139 2224000
98 AIGROEG 341 5456000 98 AIGROEG 341 5456000
111 AIHPOS 321 5136000 111 AIHPOS 321 5136000
179 AILUJ 228 3648000 179 AILUJ 228 3648000
11 AIRAM 478 7648000 11 AIRAM 478 7648000
227 AIT 147 2352000 227 AIT 147 2352000
78 AIVILO 377 6032000 78 AIVILO 377 6032000
122 ALEX 302 4832000 122 ALEX 302 4832000
185 ALEXANDRA 216 3456000 185 ALEXANDRA 216 3456000
44 ALICE 419 6704000 44 ALICE 419 6704000
247 ALICIA 113 1808000 247 ALICIA 113 1808000
22 ALISHA 457 7312000 22 ALISHA 457 7312000
132 ALLE 295 4720000 132 ALLE 295 4720000
114 ALLEBASI 320 5120000 114 ALLEBASI 320 5120000
245 ALSI 117 1872000 245 ALSI 117 1872000
215 AMBER 165 2640000 215 AMBER 165 2640000
23 AMELIA 456 7296000 23 AMELIA 456 7296000
42 AMME 426 6816000 42 AMME 426 6816000
79 ANNA 377 6032000 79 ANNA 377 6032000
196 ARAZ 193 3088000 196 ARAZ 193 3088000
202 ARIEK 178 2848000 202 ARIEK 178 2848000
243 AUHSOJ 120 1920000 243 AUHSOJ 120 1920000
84 AYAM 373 5968000 84 AYAM 373 5968000
71 BEN 388 6208000 71 BEN 388 6208000
181 BENJAMIN 223 3568000 181 BENJAMIN 223 3568000
10 BETHANY 480 7680000 10 BETHANY 480 7680000
204 BILLY 176 2816000 204 BILLY 176 2816000
45 BLAKE 418 6688000 45 BLAKE 418 6688000
61 BOCAJ 394 6304000 61 BOCAJ 394 6304000
151 BRADLEY 261 4176000 151 BRADLEY 261 4176000
103 BRANDON 337 5392000 103 BRANDON 337 5392000
7 CAASI 485 7760000 7 CAASI 485 7760000
80 CAITLIN 376 6016000 80 CAITLIN 376 6016000
108 CAMERON 333 5328000 108 CAMERON 333 5328000
254 CHARLIE 101 1616000 254 CHARLIE 101 1616000
6 CHARLOTTE 487 7792000 6 CHARLOTTE 487 7792000
161 CONNOR 248 3968000 161 CONNOR 248 3968000
41 COREY 428 6848000 41 COREY 428 6848000
240 COURTNEY 124 1984000 240 COURTNEY 124 1984000
125 DAISY 299 4784000 125 DAISY 299 4784000
100 DAMMAHOM 340 5440000 100 DAMMAHOM 340 5440000
225 DANIEL 149 2384000 225 DANIEL 149 2384000
93 DAVID 351 5616000 93 DAVID 351 5616000
180 DRAWDE 225 3600000 180 DRAWDE 225 3600000
128 DYLAN 298 4768000 128 DYLAN 298 4768000
188 EBEOHP 237 3412800 188 EBEOHP 237 3412800
221 ECARG 174 2505600 221 ECARG 174 2505600
190 ECILA 232 3340800 190 ECILA 232 3340800
123 ECNEROLF 334 4809600 123 ECNEROLF 334 4809600
194 EDWARD 227 3268800 194 EDWARD 227 3268800
208 EGIAP 191 2750400 208 EGIAP 191 2750400
201 EGROEG 200 2880000 201 EGROEG 200 2880000
235 EIBBA 152 2188800 235 EIBBA 152 2188800
191 EIDDERF 231 3326400 191 EIDDERF 231 3326400
89 EIFLA 500 5760000 89 EIFLA 500 5760000
200 EIHPOS 207 2980800 200 EIHPOS 207 2980800
118 EILLE 341 4910400 118 EILLE 341 4910400
49 EILLOH 455 6552000 49 EILLOH 455 6552000
86 EILRAHC 410 5904000 86 EILRAHC 410 5904000
70 EIMAJ 433 6235200 70 EIMAJ 433 6235200
51 EISOR 450 6480000 51 EISOR 450 6480000
38 EITAK 477 6868800 38 EITAK 477 6868800
178 EKAJ 256 3686400 178 EKAJ 256 3686400
160 EKALB 276 3974400 160 EKALB 276 3974400
168 EKUL 273 3931200 168 EKUL 273 3931200
238 ELEANOR 142 2044800 238 ELEANOR 142 2044800
167 ELIZABETH 273 3931200 167 ELIZABETH 273 3931200
27 ELLIOT 498 7171200 27 ELLIOT 498 7171200
175 ELLIS 266 3830400 175 ELLIS 266 3830400
226 ELYK 164 2361600 226 ELYK 164 2361600
159 EMILIA 277 3988800 159 EMILIA 277 3988800
134 EMILY 324 4665600 134 EMILY 324 4665600
229 EMSE 160 2304000 229 EMSE 160 2304000
59 EOZ 442 6364800 59 EOZ 442 6364800
176 ESME 263 3787200 176 ESME 263 3787200
232 ETHAN 155 2232000 232 ETHAN 155 2232000
28 EVA 497 7156800 28 EVA 497 7156800
248 EVE 123 1771200 248 EVE 123 1771200
241 EVIE 137 1972800 241 EVIE 137 1972800
163 EYKS 275 3960000 163 EYKS 275 3960000
148 FAITH 262 4192000 148 FAITH 262 4192000
62 FINLEY 393 6288000 62 FINLEY 393 6288000
246 FLORENCE 116 1856000 246 FLORENCE 116 1856000
187 FRANCESCA 215 3440000 187 FRANCESCA 215 3440000
233 FREDDIE 139 2224000 233 FREDDIE 139 2224000
26 FREYA 451 7216000 26 FREYA 451 7216000
141 GRACE 277 4432000 141 GRACE 277 4432000
224 GRACIE 150 2400000 224 GRACIE 150 2400000
32 HARRIET 437 6992000 32 HARRIET 437 6992000
1 HARRY 496 7936000 1 HARRY 496 7936000
63 HARVEY 393 6288000 63 HARVEY 393 6288000
198 HAYDEN 189 3024000 198 HAYDEN 189 3024000
3 HENRY 494 7904000 3 HENRY 494 7904000
212 HOLLY 168 2688000 212 HOLLY 168 2688000
133 HPESOJ 292 4672000 133 HPESOJ 292 4672000
35 HTEBAZILE 433 6928000 35 HTEBAZILE 433 6928000
99 HTIAF 340 5440000 99 HTIAF 340 5440000
39 IMOGEN 428 6848000 39 IMOGEN 428 6848000
105 ISABEL 335 5360000 105 ISABEL 335 5360000
4 ISABELLA 492 7872000 4 ISABELLA 492 7872000
16 ISOBEL 476 7616000 16 ISOBEL 476 7616000
213 IXEL 168 2688000 213 IXEL 168 2688000
101 JACK 340 5440000 101 JACK 340 5440000
138 JACOB 285 4560000 138 JACOB 285 4560000
64 JAKE 392 6272000 64 JAKE 392 6272000
228 JAMES 147 2352000 228 JAMES 147 2352000
85 JASMINE 371 5936000 85 JASMINE 371 5936000
222 JAY 155 2480000 222 JAY 155 2480000
154 JAYDEN 256 4096000 154 JAYDEN 256 4096000
192 JESSICA 207 3312000 192 JESSICA 207 3312000
92 JOE 352 5632000 92 JOE 352 5632000
117 JOEL 310 4960000 117 JOEL 310 4960000
112 JOHN 321 5136000 112 JOHN 321 5136000
210 JULIA 170 2720000 210 JULIA 170 2720000
231 KAI 141 2256000 231 KAI 141 2256000
87 KAZ 368 5888000 87 KAZ 368 5888000
249 KIAN 110 1760000 249 KIAN 110 1760000
0 LAUREN 497 7952000 0 LAUREN 497 7952000
152 LAYLA 261 4176000 152 LAYLA 261 4176000
58 LEAH 499 6387200 58 LEAH 499 6387200
136 LEBASI 288 4608000 136 LEBASI 288 4608000
244 LEBOSI 119 1904000 244 LEBOSI 119 1904000
120 LEOJ 303 4848000 120 LEOJ 303 4848000
218 LEXIE 162 2592000 218 LEXIE 162 2592000
47 LIAGIBA 412 6592000 47 LIAGIBA 412 6592000
40 LIAM 428 6848000 40 LIAM 428 6848000
53 LIBBY 404 6464000 53 LIBBY 404 6464000
116 LILLY 316 5056000 116 LILLY 316 5056000
104 LILY 337 5392000 104 LILY 337 5392000
37 LOGAN 432 6912000 37 LOGAN 432 6912000
144 LOLA 271 4336000 144 LOLA 271 4336000
13 LOUIS 477 7632000 13 LOUIS 477 7632000
90 LUCA 360 5760000 90 LUCA 360 5760000
36 LUCAS 432 6912000 36 LUCAS 432 6912000
153 LUKE 258 4128000 153 LUKE 258 4128000
184 LYDIA 218 3488000 184 LYDIA 218 3488000
121 MADA 303 4848000 121 MADA 303 4848000
209 MAILLIW 171 2736000 209 MAILLIW 171 2736000
165 MAISIE 247 3952000 165 MAISIE 247 3952000
170 MARIA 244 3904000 170 MARIA 244 3904000
83 MARTHA 374 5984000 83 MARTHA 374 5984000
216 MATILDA 163 2608000 216 MATILDA 163 2608000
251 MAX 107 1712000 251 MAX 107 1712000
211 MAYA 169 2704000 211 MAYA 169 2704000
207 MICHAEL 172 2752000 207 MICHAEL 172 2752000
130 MILLIE 295 4720000 130 MILLIE 295 4720000
56 MOHAMMAD 400 6400000 56 MOHAMMAD 400 6400000
236 MOHAMMED 133 2128000 236 MOHAMMED 133 2128000
68 MOLLY 390 6240000 68 MOLLY 390 6240000
12 MORGAN 478 7648000 12 MORGAN 478 7648000
65 MUHAMMAD 392 6272000 65 MUHAMMAD 392 6272000
124 MULLAC 300 4800000 124 MULLAC 300 4800000
110 NAES 324 5184000 110 NAES 324 5184000
97 NAGEM 343 5488000 97 NAGEM 343 5488000
24 NAGOL 453 7248000 24 NAGOL 453 7248000
137 NAGROM 288 4608000 137 NAGROM 288 4608000
171 NAHTE 244 3904000 171 NAHTE 244 3904000
21 NAIK 463 7408000 21 NAIK 463 7408000
143 NAITSABES 273 4368000 143 NAITSABES 273 4368000
206 NAREIK 174 2784000 206 NAREIK 174 2784000
25 NATHAN 453 7248000 25 NATHAN 453 7248000
253 NAVE 103 1648000 253 NAVE 103 1648000
57 NAWE 499 6387200 57 NAWE 499 6387200
150 NEB 261 4176000 150 NEB 261 4176000
95 NEBUER 345 5520000 95 NEBUER 345 5520000
158 NEDYAH 250 4000000 158 NEDYAH 250 4000000
131 NEDYAJ 295 4720000 131 NEDYAJ 295 4720000
193 NIAMH 205 3280000 193 NIAMH 205 3280000
109 NICOLE 329 5264000 109 NICOLE 329 5264000
250 NILTIAC 109 1744000 250 NILTIAC 109 1744000
135 NIMAJNEB 291 4656000 135 NIMAJNEB 291 4656000
147 NIRE 263 4208000 147 NIRE 263 4208000
46 NODNARB 415 6640000 46 NODNARB 415 6640000
174 NOEL 240 3840000 174 NOEL 240 3840000
50 NORAA 406 6496000 50 NORAA 406 6496000
5 NOSAM 489 7824000 5 NOSAM 489 7824000
74 NOSIDAM 384 6144000 74 NOSIDAM 384 6144000
205 NOSIDDAM 174 2784000 205 NOSIDDAM 174 2784000
164 NOSIRRAH 247 3952000 164 NOSIRRAH 247 3952000
77 NOTHSA 381 6096000 77 NOTHSA 381 6096000
106 NYLEVE 334 5344000 106 NYLEVE 334 5344000
214 OEL 167 2672000 214 OEL 167 2672000
177 OLIVIA 235 3760000 177 OLIVIA 235 3760000
169 OSCAR 245 3920000 169 OSCAR 245 3920000
43 OWEN 422 6752000 43 OWEN 422 6752000
162 PHOEBE 248 3968000 162 PHOEBE 248 3968000
66 POPPY 392 6272000 66 POPPY 392 6272000
142 RACSO 273 4368000 142 RACSO 273 4368000
140 REBECCA 277 4432000 140 REBECCA 277 4432000
19 REBMA 466 7456000 19 REBMA 466 7456000
54 REECE 404 6464000 54 REECE 404 6464000
81 REUBEN 376 6016000 81 REUBEN 376 6016000
139 RILEY 284 4544000 139 RILEY 284 4544000
189 ROBERT 212 3392000 189 ROBERT 212 3392000
183 ROLYAT 219 3504000 183 ROLYAT 219 3504000
69 RONNOC 390 6240000 69 RONNOC 390 6240000
60 RUBY 396 6336000 60 RUBY 396 6336000
239 RYAN 125 2000000 239 RYAN 125 2000000
48 SACUL 410 6560000 48 SACUL 410 6560000
127 SAM 298 4768000 127 SAM 298 4768000
107 SAMOHT 333 5328000 107 SAMOHT 333 5328000
76 SARAH 382 6112000 76 SARAH 382 6112000
94 SEBASTIAN 349 5584000 94 SEBASTIAN 349 5584000
52 SEMAJ 405 6480000 52 SEMAJ 405 6480000
8 SIENNA 485 7760000 8 SIENNA 485 7760000
199 SILLE 187 2992000 199 SILLE 187 2992000
73 SIWEL 385 6160000 73 SIWEL 385 6160000
91 SKYE 355 5680000 91 SKYE 355 5680000
113 SOPHIE 320 5120000 113 SOPHIE 320 5120000
157 SUMMER 252 4032000 157 SUMMER 252 4032000
166 SYHR 247 3952000 166 SYHR 247 3952000
230 TAYLOR 142 2272000 230 TAYLOR 142 2272000
237 THOMAS 132 2112000 237 THOMAS 132 2112000
220 TIA 157 2512000 220 TIA 157 2512000
173 TILLY 241 3856000 173 TILLY 241 3856000
119 TOBY 305 4880000 119 TOBY 305 4880000
242 TOILLE 122 1952000 242 TOILLE 122 1952000
72 TTELRACS 386 6176000 72 TTELRACS 386 6176000
75 WEHTTAM 383 6128000 75 WEHTTAM 383 6128000
182 WILLIAM 220 3520000 182 WILLIAM 220 3520000
145 XAM 268 4288000 145 XAM 268 4288000
219 XELA 160 2560000 219 XELA 160 2560000
31 YAJ 443 7088000 31 YAJ 443 7088000
88 YALNIF 365 5840000 88 YALNIF 365 5840000
146 YBBIL 264 4224000 146 YBBIL 264 4224000
67 YBOT 392 6272000 67 YBOT 392 6272000
82 YBUR 374 5984000 82 YBUR 374 5984000
33 YCUL 437 6992000 33 YCUL 437 6992000
18 YECAL 468 7488000 18 YECAL 468 7488000
15 YELIAB 476 7616000 15 YELIAB 476 7616000
30 YELIR 445 7120000 30 YELIR 445 7120000
115 YENTRUOC 318 5088000 115 YENTRUOC 318 5088000
203 YEROC 177 2832000 203 YEROC 177 2832000
34 YLIL 436 6976000 34 YLIL 436 6976000
29 YLIME 446 7136000 29 YLIME 446 7136000
96 YLLIB 344 5504000 96 YLLIB 344 5504000
155 YLLIT 253 4048000 155 YLLIT 253 4048000
9 YLLOH 481 7696000 9 YLLOH 481 7696000
14 YMA 477 7632000 14 YMA 477 7632000
149 YNAHTEB 262 4192000 149 YNAHTEB 262 4192000
2 YPPOP 495 7920000 2 YPPOP 495 7920000
252 YRAHCAZ 107 1712000 252 YRAHCAZ 107 1712000
126 YRRAH 298 4768000 126 YRRAH 298 4768000
102 YSIAD 340 5440000 102 YSIAD 340 5440000
195 ZACHARY 194 3104000 195 ZACHARY 194 3104000
55 ZARA 401 6416000 55 ZARA 401 6416000
197 ZOE 193 3088000 197 ZOE 193 3088000
%% Cell type:code id: tags: %% Cell type:code id: tags:
``` python ``` python
print(customers.sort_values(['jumlah','nama','harga'])) print(customers.sort_values(['jumlah','nama','harga']))
``` ```
%%%% Output: stream %%%% Output: stream
nama jumlah harga nama jumlah harga
254 CHARLIE 101 1616000 254 CHARLIE 101 1616000
253 NAVE 103 1648000 253 NAVE 103 1648000
251 MAX 107 1712000 251 MAX 107 1712000
252 YRAHCAZ 107 1712000 252 YRAHCAZ 107 1712000
250 NILTIAC 109 1744000 250 NILTIAC 109 1744000
249 KIAN 110 1760000 249 KIAN 110 1760000
247 ALICIA 113 1808000 247 ALICIA 113 1808000
246 FLORENCE 116 1856000 246 FLORENCE 116 1856000
245 ALSI 117 1872000 245 ALSI 117 1872000
244 LEBOSI 119 1904000 244 LEBOSI 119 1904000
243 AUHSOJ 120 1920000 243 AUHSOJ 120 1920000
242 TOILLE 122 1952000 242 TOILLE 122 1952000
248 EVE 123 1771200 248 EVE 123 1771200
240 COURTNEY 124 1984000 240 COURTNEY 124 1984000
239 RYAN 125 2000000 239 RYAN 125 2000000
237 THOMAS 132 2112000 237 THOMAS 132 2112000
236 MOHAMMED 133 2128000 236 MOHAMMED 133 2128000
241 EVIE 137 1972800 241 EVIE 137 1972800
234 AHTRAM 139 2224000 234 AHTRAM 139 2224000
233 FREDDIE 139 2224000 233 FREDDIE 139 2224000
231 KAI 141 2256000 231 KAI 141 2256000
238 ELEANOR 142 2044800 238 ELEANOR 142 2044800
230 TAYLOR 142 2272000 230 TAYLOR 142 2272000
227 AIT 147 2352000 227 AIT 147 2352000
228 JAMES 147 2352000 228 JAMES 147 2352000
225 DANIEL 149 2384000 225 DANIEL 149 2384000
224 GRACIE 150 2400000 224 GRACIE 150 2400000
223 ADAM 152 2432000 223 ADAM 152 2432000
235 EIBBA 152 2188800 235 EIBBA 152 2188800
232 ETHAN 155 2232000 232 ETHAN 155 2232000
222 JAY 155 2480000 222 JAY 155 2480000
220 TIA 157 2512000 220 TIA 157 2512000
229 EMSE 160 2304000 229 EMSE 160 2304000
219 XELA 160 2560000 219 XELA 160 2560000
218 LEXIE 162 2592000 218 LEXIE 162 2592000
217 AHSILA 163 2608000 217 AHSILA 163 2608000
216 MATILDA 163 2608000 216 MATILDA 163 2608000
226 ELYK 164 2361600 226 ELYK 164 2361600
215 AMBER 165 2640000 215 AMBER 165 2640000
214 OEL 167 2672000 214 OEL 167 2672000
212 HOLLY 168 2688000 212 HOLLY 168 2688000
213 IXEL 168 2688000 213 IXEL 168 2688000
211 MAYA 169 2704000 211 MAYA 169 2704000
210 JULIA 170 2720000 210 JULIA 170 2720000
209 MAILLIW 171 2736000 209 MAILLIW 171 2736000
207 MICHAEL 172 2752000 207 MICHAEL 172 2752000
221 ECARG 174 2505600 221 ECARG 174 2505600
206 NAREIK 174 2784000 206 NAREIK 174 2784000
205 NOSIDDAM 174 2784000 205 NOSIDDAM 174 2784000
204 BILLY 176 2816000 204 BILLY 176 2816000
203 YEROC 177 2832000 203 YEROC 177 2832000
202 ARIEK 178 2848000 202 ARIEK 178 2848000
199 SILLE 187 2992000 199 SILLE 187 2992000
198 HAYDEN 189 3024000 198 HAYDEN 189 3024000
208 EGIAP 191 2750400 208 EGIAP 191 2750400
196 ARAZ 193 3088000 196 ARAZ 193 3088000
197 ZOE 193 3088000 197 ZOE 193 3088000
195 ZACHARY 194 3104000 195 ZACHARY 194 3104000
201 EGROEG 200 2880000 201 EGROEG 200 2880000
193 NIAMH 205 3280000 193 NIAMH 205 3280000
200 EIHPOS 207 2980800 200 EIHPOS 207 2980800
192 JESSICA 207 3312000 192 JESSICA 207 3312000
189 ROBERT 212 3392000 189 ROBERT 212 3392000
186 ACISSEJ 215 3440000 186 ACISSEJ 215 3440000
187 FRANCESCA 215 3440000 187 FRANCESCA 215 3440000
185 ALEXANDRA 216 3456000 185 ALEXANDRA 216 3456000
184 LYDIA 218 3488000 184 LYDIA 218 3488000
183 ROLYAT 219 3504000 183 ROLYAT 219 3504000
182 WILLIAM 220 3520000 182 WILLIAM 220 3520000
181 BENJAMIN 223 3568000 181 BENJAMIN 223 3568000
180 DRAWDE 225 3600000 180 DRAWDE 225 3600000
194 EDWARD 227 3268800 194 EDWARD 227 3268800
179 AILUJ 228 3648000 179 AILUJ 228 3648000
191 EIDDERF 231 3326400 191 EIDDERF 231 3326400
190 ECILA 232 3340800 190 ECILA 232 3340800
177 OLIVIA 235 3760000 177 OLIVIA 235 3760000
188 EBEOHP 237 3412800 188 EBEOHP 237 3412800
174 NOEL 240 3840000 174 NOEL 240 3840000
173 TILLY 241 3856000 173 TILLY 241 3856000
172 AARON 243 3888000 172 AARON 243 3888000
170 MARIA 244 3904000 170 MARIA 244 3904000
171 NAHTE 244 3904000 171 NAHTE 244 3904000
169 OSCAR 245 3920000 169 OSCAR 245 3920000
165 MAISIE 247 3952000 165 MAISIE 247 3952000
164 NOSIRRAH 247 3952000 164 NOSIRRAH 247 3952000
166 SYHR 247 3952000 166 SYHR 247 3952000
161 CONNOR 248 3968000 161 CONNOR 248 3968000
162 PHOEBE 248 3968000 162 PHOEBE 248 3968000
158 NEDYAH 250 4000000 158 NEDYAH 250 4000000
157 SUMMER 252 4032000 157 SUMMER 252 4032000
156 ACSECNARF 253 4048000 156 ACSECNARF 253 4048000
155 YLLIT 253 4048000 155 YLLIT 253 4048000
178 EKAJ 256 3686400 178 EKAJ 256 3686400
154 JAYDEN 256 4096000 154 JAYDEN 256 4096000
153 LUKE 258 4128000 153 LUKE 258 4128000
151 BRADLEY 261 4176000 151 BRADLEY 261 4176000
152 LAYLA 261 4176000 152 LAYLA 261 4176000
150 NEB 261 4176000 150 NEB 261 4176000
148 FAITH 262 4192000 148 FAITH 262 4192000
149 YNAHTEB 262 4192000 149 YNAHTEB 262 4192000
176 ESME 263 3787200 176 ESME 263 3787200
147 NIRE 263 4208000 147 NIRE 263 4208000
146 YBBIL 264 4224000 146 YBBIL 264 4224000
175 ELLIS 266 3830400 175 ELLIS 266 3830400
145 XAM 268 4288000 145 XAM 268 4288000
144 LOLA 271 4336000 144 LOLA 271 4336000
168 EKUL 273 3931200 168 EKUL 273 3931200
167 ELIZABETH 273 3931200 167 ELIZABETH 273 3931200
143 NAITSABES 273 4368000 143 NAITSABES 273 4368000
142 RACSO 273 4368000 142 RACSO 273 4368000
163 EYKS 275 3960000 163 EYKS 275 3960000
160 EKALB 276 3974400 160 EKALB 276 3974400
159 EMILIA 277 3988800 159 EMILIA 277 3988800
141 GRACE 277 4432000 141 GRACE 277 4432000
140 REBECCA 277 4432000 140 REBECCA 277 4432000
139 RILEY 284 4544000 139 RILEY 284 4544000
138 JACOB 285 4560000 138 JACOB 285 4560000
136 LEBASI 288 4608000 136 LEBASI 288 4608000
137 NAGROM 288 4608000 137 NAGROM 288 4608000
135 NIMAJNEB 291 4656000 135 NIMAJNEB 291 4656000
133 HPESOJ 292 4672000 133 HPESOJ 292 4672000
132 ALLE 295 4720000 132 ALLE 295 4720000
130 MILLIE 295 4720000 130 MILLIE 295 4720000
131 NEDYAJ 295 4720000 131 NEDYAJ 295 4720000
129 ACUL 296 4736000 129 ACUL 296 4736000
128 DYLAN 298 4768000 128 DYLAN 298 4768000
127 SAM 298 4768000 127 SAM 298 4768000
126 YRRAH 298 4768000 126 YRRAH 298 4768000
125 DAISY 299 4784000 125 DAISY 299 4784000
124 MULLAC 300 4800000 124 MULLAC 300 4800000
122 ALEX 302 4832000 122 ALEX 302 4832000
120 LEOJ 303 4848000 120 LEOJ 303 4848000
121 MADA 303 4848000 121 MADA 303 4848000
119 TOBY 305 4880000 119 TOBY 305 4880000
117 JOEL 310 4960000 117 JOEL 310 4960000
116 LILLY 316 5056000 116 LILLY 316 5056000
115 YENTRUOC 318 5088000 115 YENTRUOC 318 5088000
114 ALLEBASI 320 5120000 114 ALLEBASI 320 5120000
113 SOPHIE 320 5120000 113 SOPHIE 320 5120000
111 AIHPOS 321 5136000 111 AIHPOS 321 5136000
112 JOHN 321 5136000 112 JOHN 321 5136000
134 EMILY 324 4665600 134 EMILY 324 4665600
110 NAES 324 5184000 110 NAES 324 5184000
109 NICOLE 329 5264000 109 NICOLE 329 5264000
108 CAMERON 333 5328000 108 CAMERON 333 5328000
107 SAMOHT 333 5328000 107 SAMOHT 333 5328000
123 ECNEROLF 334 4809600 123 ECNEROLF 334 4809600
106 NYLEVE 334 5344000 106 NYLEVE 334 5344000
105 ISABEL 335 5360000 105 ISABEL 335 5360000
103 BRANDON 337 5392000 103 BRANDON 337 5392000
104 LILY 337 5392000 104 LILY 337 5392000
100 DAMMAHOM 340 5440000 100 DAMMAHOM 340 5440000
99 HTIAF 340 5440000 99 HTIAF 340 5440000
101 JACK 340 5440000 101 JACK 340 5440000
102 YSIAD 340 5440000 102 YSIAD 340 5440000
98 AIGROEG 341 5456000 98 AIGROEG 341 5456000
118 EILLE 341 4910400 118 EILLE 341 4910400
97 NAGEM 343 5488000 97 NAGEM 343 5488000
96 YLLIB 344 5504000 96 YLLIB 344 5504000
95 NEBUER 345 5520000 95 NEBUER 345 5520000
94 SEBASTIAN 349 5584000 94 SEBASTIAN 349 5584000
93 DAVID 351 5616000 93 DAVID 351 5616000
92 JOE 352 5632000 92 JOE 352 5632000
91 SKYE 355 5680000 91 SKYE 355 5680000
90 LUCA 360 5760000 90 LUCA 360 5760000
88 YALNIF 365 5840000 88 YALNIF 365 5840000
87 KAZ 368 5888000 87 KAZ 368 5888000
85 JASMINE 371 5936000 85 JASMINE 371 5936000
84 AYAM 373 5968000 84 AYAM 373 5968000
83 MARTHA 374 5984000 83 MARTHA 374 5984000
82 YBUR 374 5984000 82 YBUR 374 5984000
80 CAITLIN 376 6016000 80 CAITLIN 376 6016000
81 REUBEN 376 6016000 81 REUBEN 376 6016000
78 AIVILO 377 6032000 78 AIVILO 377 6032000
79 ANNA 377 6032000 79 ANNA 377 6032000
77 NOTHSA 381 6096000 77 NOTHSA 381 6096000
76 SARAH 382 6112000 76 SARAH 382 6112000
75 WEHTTAM 383 6128000 75 WEHTTAM 383 6128000
74 NOSIDAM 384 6144000 74 NOSIDAM 384 6144000
73 SIWEL 385 6160000 73 SIWEL 385 6160000
72 TTELRACS 386 6176000 72 TTELRACS 386 6176000
71 BEN 388 6208000 71 BEN 388 6208000
68 MOLLY 390 6240000 68 MOLLY 390 6240000
69 RONNOC 390 6240000 69 RONNOC 390 6240000
64 JAKE 392 6272000 64 JAKE 392 6272000
65 MUHAMMAD 392 6272000 65 MUHAMMAD 392 6272000
66 POPPY 392 6272000 66 POPPY 392 6272000
67 YBOT 392 6272000 67 YBOT 392 6272000
62 FINLEY 393 6288000 62 FINLEY 393 6288000
63 HARVEY 393 6288000 63 HARVEY 393 6288000
61 BOCAJ 394 6304000 61 BOCAJ 394 6304000
60 RUBY 396 6336000 60 RUBY 396 6336000
56 MOHAMMAD 400 6400000 56 MOHAMMAD 400 6400000
55 ZARA 401 6416000 55 ZARA 401 6416000
53 LIBBY 404 6464000 53 LIBBY 404 6464000
54 REECE 404 6464000 54 REECE 404 6464000
52 SEMAJ 405 6480000 52 SEMAJ 405 6480000
50 NORAA 406 6496000 50 NORAA 406 6496000
86 EILRAHC 410 5904000 86 EILRAHC 410 5904000
48 SACUL 410 6560000 48 SACUL 410 6560000
47 LIAGIBA 412 6592000 47 LIAGIBA 412 6592000
46 NODNARB 415 6640000 46 NODNARB 415 6640000
45 BLAKE 418 6688000 45 BLAKE 418 6688000
44 ALICE 419 6704000 44 ALICE 419 6704000
43 OWEN 422 6752000 43 OWEN 422 6752000
42 AMME 426 6816000 42 AMME 426 6816000
41 COREY 428 6848000 41 COREY 428 6848000
39 IMOGEN 428 6848000 39 IMOGEN 428 6848000
40 LIAM 428 6848000 40 LIAM 428 6848000
37 LOGAN 432 6912000 37 LOGAN 432 6912000
36 LUCAS 432 6912000 36 LUCAS 432 6912000
70 EIMAJ 433 6235200 70 EIMAJ 433 6235200
35 HTEBAZILE 433 6928000 35 HTEBAZILE 433 6928000
34 YLIL 436 6976000 34 YLIL 436 6976000
32 HARRIET 437 6992000 32 HARRIET 437 6992000
33 YCUL 437 6992000 33 YCUL 437 6992000
59 EOZ 442 6364800 59 EOZ 442 6364800
31 YAJ 443 7088000 31 YAJ 443 7088000
30 YELIR 445 7120000 30 YELIR 445 7120000
29 YLIME 446 7136000 29 YLIME 446 7136000
51 EISOR 450 6480000 51 EISOR 450 6480000
26 FREYA 451 7216000 26 FREYA 451 7216000
24 NAGOL 453 7248000 24 NAGOL 453 7248000
25 NATHAN 453 7248000 25 NATHAN 453 7248000
49 EILLOH 455 6552000 49 EILLOH 455 6552000
23 AMELIA 456 7296000 23 AMELIA 456 7296000
22 ALISHA 457 7312000 22 ALISHA 457 7312000
20 ACCEBER 463 7408000 20 ACCEBER 463 7408000
21 NAIK 463 7408000 21 NAIK 463 7408000
19 REBMA 466 7456000 19 REBMA 466 7456000
18 YECAL 468 7488000 18 YECAL 468 7488000
17 ADLITAM 474 7584000 17 ADLITAM 474 7584000
16 ISOBEL 476 7616000 16 ISOBEL 476 7616000
15 YELIAB 476 7616000 15 YELIAB 476 7616000
38 EITAK 477 6868800 38 EITAK 477 6868800
13 LOUIS 477 7632000 13 LOUIS 477 7632000
14 YMA 477 7632000 14 YMA 477 7632000
11 AIRAM 478 7648000 11 AIRAM 478 7648000
12 MORGAN 478 7648000 12 MORGAN 478 7648000
10 BETHANY 480 7680000 10 BETHANY 480 7680000
9 YLLOH 481 7696000 9 YLLOH 481 7696000
7 CAASI 485 7760000 7 CAASI 485 7760000
8 SIENNA 485 7760000 8 SIENNA 485 7760000
6 CHARLOTTE 487 7792000 6 CHARLOTTE 487 7792000
5 NOSAM 489 7824000 5 NOSAM 489 7824000
4 ISABELLA 492 7872000 4 ISABELLA 492 7872000
3 HENRY 494 7904000 3 HENRY 494 7904000
2 YPPOP 495 7920000 2 YPPOP 495 7920000
1 HARRY 496 7936000 1 HARRY 496 7936000
28 EVA 497 7156800 28 EVA 497 7156800
0 LAUREN 497 7952000 0 LAUREN 497 7952000
27 ELLIOT 498 7171200 27 ELLIOT 498 7171200
58 LEAH 499 6387200 58 LEAH 499 6387200
57 NAWE 499 6387200 57 NAWE 499 6387200
89 EIFLA 500 5760000 89 EIFLA 500 5760000
%% Cell type:markdown id: tags: %% Cell type:markdown id: tags:
saat urutannya diubah maka proses pengurutannya mengikuti urutan title yang disebutkan saat urutannya diubah maka proses pengurutannya mengikuti urutan title yang disebutkan
%% Cell type:code id: tags: %% Cell type:code id: tags:
``` python ``` python
import matplotlib.pyplot as plt import matplotlib.pyplot as plt
plt.hist(customers['jumlah'], bins= 10, edgecolor='black') plt.hist(customers['jumlah'], bins= 10, edgecolor='black')
plt.title("Diagram Jumlah Order") plt.title("Diagram Jumlah Order")
plt.xlabel("Order") plt.xlabel("Order")
plt.ylabel("Frekuensi") plt.ylabel("Frekuensi")
plt.show() plt.show()
``` ```
%%%% Output: display_data %%%% Output: display_data
[Hidden Image Output] [Hidden Image Output]
%% Cell type:code id: tags: %% Cell type:code id: tags:
``` python ``` python
plt.hist(customers['jumlah'], bins= 100, edgecolor='black') plt.hist(customers['jumlah'], bins= 100, edgecolor='black')
plt.title("Diagram Jumlah Order") plt.title("Diagram Jumlah Order")
plt.xlabel("Order") plt.xlabel("Order")
plt.ylabel("Frekuensi") plt.ylabel("Frekuensi")
plt.show() plt.show()
``` ```
%%%% Output: display_data %%%% Output: display_data
[Hidden Image Output] [Hidden Image Output]
%% Cell type:code id: tags: %% Cell type:code id: tags:
``` python ``` python
plt.hist(customers['nama'], bins= 10, edgecolor='black') plt.hist(customers['nama'], bins= 10, edgecolor='black')
plt.title("Diagram Jumlah Order") plt.title("Diagram nama")
plt.xlabel("Order") plt.xlabel("Order")
plt.ylabel("Frekuensi") plt.ylabel("Frekuensi")
plt.show() plt.show()
``` ```
%%%% Output: display_data %%%% Output: display_data
[Hidden Image Output] [Hidden Image Output]
%% Cell type:markdown id: tags: %% Cell type:markdown id: tags:
Visualisasi 'nama' tidak cocok menggunakan histogram Visualisasi 'nama' tidak cocok menggunakan histogram
......
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