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calculadora_impuestos
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tcapelle commited on
Commit
ba1a530
•
1 Parent(s): 9570030

agregar rgafico

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Files changed (3) hide show
  1. app.py +3 -3
  2. calc.ipynb +1137 -48
  3. impuestos.py +12 -0
app.py CHANGED
@@ -2,7 +2,7 @@ from pathlib import Path
2
  from types import SimpleNamespace
3
  import streamlit as st
4
 
5
- from impuestos import TRAMOS, TRAMOS_REFORMA, get_table
6
 
7
  TOPES = SimpleNamespace(arriendo=450000, cuidado=550000)
8
 
@@ -54,8 +54,8 @@ def main() -> None:
54
  total_reforma = table["Impuesto"].sum()
55
  col2.subheader(f"Total Impuesto con Reforma: ${total_reforma} ({100*(total_reforma/sueldo_bruto):.2f}\%)")
56
 
57
-
58
- # st.plotly_chart()
59
 
60
  if __name__ == "__main__":
61
  st.set_page_config(
 
2
  from types import SimpleNamespace
3
  import streamlit as st
4
 
5
+ from impuestos import TRAMOS, TRAMOS_REFORMA, get_table, get_curve
6
 
7
  TOPES = SimpleNamespace(arriendo=450000, cuidado=550000)
8
 
 
54
  total_reforma = table["Impuesto"].sum()
55
  col2.subheader(f"Total Impuesto con Reforma: ${total_reforma} ({100*(total_reforma/sueldo_bruto):.2f}\%)")
56
 
57
+ st.text("En el siguiente grafico se ve claramente que la reforma empieza a tener efecto a partir de los 4 millones. Por ejemplo con 8 millones mensuales la diferencia es solo de 200000 mensual.")
58
+ st.plotly_chart(get_curve(0), use_container_width=True)
59
 
60
  if __name__ == "__main__":
61
  st.set_page_config(
calc.ipynb CHANGED
@@ -2,7 +2,7 @@
2
  "cells": [
3
  {
4
  "cell_type": "code",
5
- "execution_count": 1,
6
  "metadata": {},
7
  "outputs": [],
8
  "source": [
@@ -11,15 +11,15 @@
11
  },
12
  {
13
  "cell_type": "code",
14
- "execution_count": 2,
15
  "metadata": {},
16
  "outputs": [
17
  {
18
  "name": "stdout",
19
  "output_type": "stream",
20
  "text": [
21
- "786384 0\n",
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- "1747440 0.04\n"
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  ]
24
  }
25
  ],
@@ -37,16 +37,16 @@
37
  },
38
  {
39
  "cell_type": "code",
40
- "execution_count": 3,
41
  "metadata": {},
42
  "outputs": [
43
  {
44
  "data": {
45
  "text/plain": [
46
- "[786384, 1747440, 2912400, 4077360, 5242320, 6989760, 18056880, 99999999]"
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  ]
48
  },
49
- "execution_count": 3,
50
  "metadata": {},
51
  "output_type": "execute_result"
52
  }
@@ -57,7 +57,7 @@
57
  },
58
  {
59
  "cell_type": "code",
60
- "execution_count": 18,
61
  "metadata": {},
62
  "outputs": [],
63
  "source": [
@@ -76,16 +76,16 @@
76
  },
77
  {
78
  "cell_type": "code",
79
- "execution_count": 19,
80
  "metadata": {},
81
  "outputs": [
82
  {
83
  "data": {
84
  "text/plain": [
85
- "([786384, 413616], [0, 16544])"
86
  ]
87
  },
88
- "execution_count": 19,
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  "metadata": {},
90
  "output_type": "execute_result"
91
  }
@@ -97,7 +97,7 @@
97
  },
98
  {
99
  "cell_type": "code",
100
- "execution_count": 20,
101
  "metadata": {},
102
  "outputs": [],
103
  "source": [
@@ -106,7 +106,7 @@
106
  },
107
  {
108
  "cell_type": "code",
109
- "execution_count": 21,
110
  "metadata": {},
111
  "outputs": [],
112
  "source": [
@@ -120,7 +120,7 @@
120
  },
121
  {
122
  "cell_type": "code",
123
- "execution_count": 22,
124
  "metadata": {},
125
  "outputs": [
126
  {
@@ -155,58 +155,58 @@
155
  " <tr>\n",
156
  " <th>0</th>\n",
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  " <td>0</td>\n",
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- " <td>786384</td>\n",
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- " <td>786384</td>\n",
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  " <td>0.000</td>\n",
161
  " <td>0</td>\n",
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  " </tr>\n",
163
  " <tr>\n",
164
  " <th>1</th>\n",
165
- " <td>786384</td>\n",
166
- " <td>1747440</td>\n",
167
- " <td>961056</td>\n",
168
  " <td>0.040</td>\n",
169
- " <td>38442</td>\n",
170
  " </tr>\n",
171
  " <tr>\n",
172
  " <th>2</th>\n",
173
- " <td>1747440</td>\n",
174
- " <td>2912400</td>\n",
175
- " <td>1164960</td>\n",
176
  " <td>0.080</td>\n",
177
- " <td>93196</td>\n",
178
  " </tr>\n",
179
  " <tr>\n",
180
  " <th>3</th>\n",
181
- " <td>2912400</td>\n",
182
- " <td>4077360</td>\n",
183
- " <td>1164960</td>\n",
184
  " <td>0.135</td>\n",
185
- " <td>157269</td>\n",
186
  " </tr>\n",
187
  " <tr>\n",
188
  " <th>4</th>\n",
189
- " <td>4077360</td>\n",
190
- " <td>5242320</td>\n",
191
- " <td>1164960</td>\n",
192
  " <td>0.230</td>\n",
193
- " <td>267940</td>\n",
194
  " </tr>\n",
195
  " <tr>\n",
196
  " <th>5</th>\n",
197
- " <td>5242320</td>\n",
198
- " <td>6989760</td>\n",
199
- " <td>1747440</td>\n",
200
  " <td>0.304</td>\n",
201
- " <td>531221</td>\n",
202
  " </tr>\n",
203
  " <tr>\n",
204
  " <th>6</th>\n",
205
- " <td>6989760</td>\n",
206
- " <td>18056880</td>\n",
207
- " <td>3010240</td>\n",
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  " <td>0.350</td>\n",
209
- " <td>1053584</td>\n",
210
  " </tr>\n",
211
  " </tbody>\n",
212
  "</table>\n",
@@ -214,16 +214,16 @@
214
  ],
215
  "text/plain": [
216
  " Desde Hasta Monto Tasa Impuesto\n",
217
- "0 0 786384 786384 0.000 0\n",
218
- "1 786384 1747440 961056 0.040 38442\n",
219
- "2 1747440 2912400 1164960 0.080 93196\n",
220
- "3 2912400 4077360 1164960 0.135 157269\n",
221
- "4 4077360 5242320 1164960 0.230 267940\n",
222
- "5 5242320 6989760 1747440 0.304 531221\n",
223
- "6 6989760 18056880 3010240 0.350 1053584"
224
  ]
225
  },
226
- "execution_count": 22,
227
  "metadata": {},
228
  "output_type": "execute_result"
229
  }
@@ -232,6 +232,1095 @@
232
  "get_table(10000000)"
233
  ]
234
  },
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
235
  {
236
  "cell_type": "code",
237
  "execution_count": null,
 
2
  "cells": [
3
  {
4
  "cell_type": "code",
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+ "execution_count": 7,
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  "metadata": {},
7
  "outputs": [],
8
  "source": [
 
11
  },
12
  {
13
  "cell_type": "code",
14
+ "execution_count": 8,
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  "metadata": {},
16
  "outputs": [
17
  {
18
  "name": "stdout",
19
  "output_type": "stream",
20
  "text": [
21
+ "777000 0\n",
22
+ "1727000 0.04\n"
23
  ]
24
  }
25
  ],
 
37
  },
38
  {
39
  "cell_type": "code",
40
+ "execution_count": 9,
41
  "metadata": {},
42
  "outputs": [
43
  {
44
  "data": {
45
  "text/plain": [
46
+ "[777000, 1727000, 2878000, 4029000, 5180000, 6906000, 17842000, 99999999]"
47
  ]
48
  },
49
+ "execution_count": 9,
50
  "metadata": {},
51
  "output_type": "execute_result"
52
  }
 
57
  },
58
  {
59
  "cell_type": "code",
60
+ "execution_count": 10,
61
  "metadata": {},
62
  "outputs": [],
63
  "source": [
 
76
  },
77
  {
78
  "cell_type": "code",
79
+ "execution_count": 11,
80
  "metadata": {},
81
  "outputs": [
82
  {
83
  "data": {
84
  "text/plain": [
85
+ "([777000, 423000], [0, 16920])"
86
  ]
87
  },
88
+ "execution_count": 11,
89
  "metadata": {},
90
  "output_type": "execute_result"
91
  }
 
97
  },
98
  {
99
  "cell_type": "code",
100
+ "execution_count": 12,
101
  "metadata": {},
102
  "outputs": [],
103
  "source": [
 
106
  },
107
  {
108
  "cell_type": "code",
109
+ "execution_count": 13,
110
  "metadata": {},
111
  "outputs": [],
112
  "source": [
 
120
  },
121
  {
122
  "cell_type": "code",
123
+ "execution_count": 14,
124
  "metadata": {},
125
  "outputs": [
126
  {
 
155
  " <tr>\n",
156
  " <th>0</th>\n",
157
  " <td>0</td>\n",
158
+ " <td>777000</td>\n",
159
+ " <td>777000</td>\n",
160
  " <td>0.000</td>\n",
161
  " <td>0</td>\n",
162
  " </tr>\n",
163
  " <tr>\n",
164
  " <th>1</th>\n",
165
+ " <td>777000</td>\n",
166
+ " <td>1727000</td>\n",
167
+ " <td>950000</td>\n",
168
  " <td>0.040</td>\n",
169
+ " <td>38000</td>\n",
170
  " </tr>\n",
171
  " <tr>\n",
172
  " <th>2</th>\n",
173
+ " <td>1727000</td>\n",
174
+ " <td>2878000</td>\n",
175
+ " <td>1151000</td>\n",
176
  " <td>0.080</td>\n",
177
+ " <td>92080</td>\n",
178
  " </tr>\n",
179
  " <tr>\n",
180
  " <th>3</th>\n",
181
+ " <td>2878000</td>\n",
182
+ " <td>4029000</td>\n",
183
+ " <td>1151000</td>\n",
184
  " <td>0.135</td>\n",
185
+ " <td>155385</td>\n",
186
  " </tr>\n",
187
  " <tr>\n",
188
  " <th>4</th>\n",
189
+ " <td>4029000</td>\n",
190
+ " <td>5180000</td>\n",
191
+ " <td>1151000</td>\n",
192
  " <td>0.230</td>\n",
193
+ " <td>264730</td>\n",
194
  " </tr>\n",
195
  " <tr>\n",
196
  " <th>5</th>\n",
197
+ " <td>5180000</td>\n",
198
+ " <td>6906000</td>\n",
199
+ " <td>1726000</td>\n",
200
  " <td>0.304</td>\n",
201
+ " <td>524704</td>\n",
202
  " </tr>\n",
203
  " <tr>\n",
204
  " <th>6</th>\n",
205
+ " <td>6906000</td>\n",
206
+ " <td>17842000</td>\n",
207
+ " <td>3094000</td>\n",
208
  " <td>0.350</td>\n",
209
+ " <td>1082900</td>\n",
210
  " </tr>\n",
211
  " </tbody>\n",
212
  "</table>\n",
 
214
  ],
215
  "text/plain": [
216
  " Desde Hasta Monto Tasa Impuesto\n",
217
+ "0 0 777000 777000 0.000 0\n",
218
+ "1 777000 1727000 950000 0.040 38000\n",
219
+ "2 1727000 2878000 1151000 0.080 92080\n",
220
+ "3 2878000 4029000 1151000 0.135 155385\n",
221
+ "4 4029000 5180000 1151000 0.230 264730\n",
222
+ "5 5180000 6906000 1726000 0.304 524704\n",
223
+ "6 6906000 17842000 3094000 0.350 1082900"
224
  ]
225
  },
226
+ "execution_count": 14,
227
  "metadata": {},
228
  "output_type": "execute_result"
229
  }
 
232
  "get_table(10000000)"
233
  ]
234
  },
235
+ {
236
+ "cell_type": "code",
237
+ "execution_count": 41,
238
+ "metadata": {},
239
+ "outputs": [],
240
+ "source": [
241
+ "salarios = [450_000, 1000_000, 1_500_000, 2_000_000, 3_000_000, 5_000_000, 8_000_000, 10_000_000, 15_000_000]"
242
+ ]
243
+ },
244
+ {
245
+ "cell_type": "code",
246
+ "execution_count": 42,
247
+ "metadata": {},
248
+ "outputs": [],
249
+ "source": [
250
+ "df = pd.DataFrame(columns=[\"actual\", \"reforma\"], index=salarios)"
251
+ ]
252
+ },
253
+ {
254
+ "cell_type": "code",
255
+ "execution_count": 43,
256
+ "metadata": {},
257
+ "outputs": [],
258
+ "source": [
259
+ "df[\"actual\"] = [sum(descomponer_en_tramos(s, TRAMOS)[1]) for s in salarios]\n",
260
+ "df[\"reforma\"] = [sum(descomponer_en_tramos(s, TRAMOS_REFORMA)[1]) for s in salarios]"
261
+ ]
262
+ },
263
+ {
264
+ "cell_type": "code",
265
+ "execution_count": 44,
266
+ "metadata": {},
267
+ "outputs": [
268
+ {
269
+ "data": {
270
+ "text/html": [
271
+ "<div>\n",
272
+ "<style scoped>\n",
273
+ " .dataframe tbody tr th:only-of-type {\n",
274
+ " vertical-align: middle;\n",
275
+ " }\n",
276
+ "\n",
277
+ " .dataframe tbody tr th {\n",
278
+ " vertical-align: top;\n",
279
+ " }\n",
280
+ "\n",
281
+ " .dataframe thead th {\n",
282
+ " text-align: right;\n",
283
+ " }\n",
284
+ "</style>\n",
285
+ "<table border=\"1\" class=\"dataframe\">\n",
286
+ " <thead>\n",
287
+ " <tr style=\"text-align: right;\">\n",
288
+ " <th></th>\n",
289
+ " <th>actual</th>\n",
290
+ " <th>reforma</th>\n",
291
+ " </tr>\n",
292
+ " </thead>\n",
293
+ " <tbody>\n",
294
+ " <tr>\n",
295
+ " <th>450000</th>\n",
296
+ " <td>0</td>\n",
297
+ " <td>0</td>\n",
298
+ " </tr>\n",
299
+ " <tr>\n",
300
+ " <th>1000000</th>\n",
301
+ " <td>8920</td>\n",
302
+ " <td>8920</td>\n",
303
+ " </tr>\n",
304
+ " <tr>\n",
305
+ " <th>1500000</th>\n",
306
+ " <td>28920</td>\n",
307
+ " <td>28920</td>\n",
308
+ " </tr>\n",
309
+ " <tr>\n",
310
+ " <th>2000000</th>\n",
311
+ " <td>59840</td>\n",
312
+ " <td>59840</td>\n",
313
+ " </tr>\n",
314
+ " <tr>\n",
315
+ " <th>3000000</th>\n",
316
+ " <td>146550</td>\n",
317
+ " <td>146550</td>\n",
318
+ " </tr>\n",
319
+ " <tr>\n",
320
+ " <th>5000000</th>\n",
321
+ " <td>508795</td>\n",
322
+ " <td>537800</td>\n",
323
+ " </tr>\n",
324
+ " <tr>\n",
325
+ " <th>8000000</th>\n",
326
+ " <td>1457799</td>\n",
327
+ " <td>1649441</td>\n",
328
+ " </tr>\n",
329
+ " <tr>\n",
330
+ " <th>10000000</th>\n",
331
+ " <td>2157799</td>\n",
332
+ " <td>2507731</td>\n",
333
+ " </tr>\n",
334
+ " <tr>\n",
335
+ " <th>15000000</th>\n",
336
+ " <td>3907799</td>\n",
337
+ " <td>4657731</td>\n",
338
+ " </tr>\n",
339
+ " </tbody>\n",
340
+ "</table>\n",
341
+ "</div>"
342
+ ],
343
+ "text/plain": [
344
+ " actual reforma\n",
345
+ "450000 0 0\n",
346
+ "1000000 8920 8920\n",
347
+ "1500000 28920 28920\n",
348
+ "2000000 59840 59840\n",
349
+ "3000000 146550 146550\n",
350
+ "5000000 508795 537800\n",
351
+ "8000000 1457799 1649441\n",
352
+ "10000000 2157799 2507731\n",
353
+ "15000000 3907799 4657731"
354
+ ]
355
+ },
356
+ "execution_count": 44,
357
+ "metadata": {},
358
+ "output_type": "execute_result"
359
+ }
360
+ ],
361
+ "source": [
362
+ "df"
363
+ ]
364
+ },
365
+ {
366
+ "cell_type": "code",
367
+ "execution_count": 45,
368
+ "metadata": {},
369
+ "outputs": [],
370
+ "source": [
371
+ "import plotly.express as px"
372
+ ]
373
+ },
374
+ {
375
+ "cell_type": "code",
376
+ "execution_count": 46,
377
+ "metadata": {},
378
+ "outputs": [
379
+ {
380
+ "data": {
381
+ "application/vnd.plotly.v1+json": {
382
+ "config": {
383
+ "plotlyServerURL": "https://plot.ly"
384
+ },
385
+ "data": [
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+ "bgcolor": "white",
1186
+ "lakecolor": "white",
1187
+ "landcolor": "#E5ECF6",
1188
+ "showlakes": true,
1189
+ "showland": true,
1190
+ "subunitcolor": "white"
1191
+ },
1192
+ "hoverlabel": {
1193
+ "align": "left"
1194
+ },
1195
+ "hovermode": "closest",
1196
+ "mapbox": {
1197
+ "style": "light"
1198
+ },
1199
+ "paper_bgcolor": "white",
1200
+ "plot_bgcolor": "#E5ECF6",
1201
+ "polar": {
1202
+ "angularaxis": {
1203
+ "gridcolor": "white",
1204
+ "linecolor": "white",
1205
+ "ticks": ""
1206
+ },
1207
+ "bgcolor": "#E5ECF6",
1208
+ "radialaxis": {
1209
+ "gridcolor": "white",
1210
+ "linecolor": "white",
1211
+ "ticks": ""
1212
+ }
1213
+ },
1214
+ "scene": {
1215
+ "xaxis": {
1216
+ "backgroundcolor": "#E5ECF6",
1217
+ "gridcolor": "white",
1218
+ "gridwidth": 2,
1219
+ "linecolor": "white",
1220
+ "showbackground": true,
1221
+ "ticks": "",
1222
+ "zerolinecolor": "white"
1223
+ },
1224
+ "yaxis": {
1225
+ "backgroundcolor": "#E5ECF6",
1226
+ "gridcolor": "white",
1227
+ "gridwidth": 2,
1228
+ "linecolor": "white",
1229
+ "showbackground": true,
1230
+ "ticks": "",
1231
+ "zerolinecolor": "white"
1232
+ },
1233
+ "zaxis": {
1234
+ "backgroundcolor": "#E5ECF6",
1235
+ "gridcolor": "white",
1236
+ "gridwidth": 2,
1237
+ "linecolor": "white",
1238
+ "showbackground": true,
1239
+ "ticks": "",
1240
+ "zerolinecolor": "white"
1241
+ }
1242
+ },
1243
+ "shapedefaults": {
1244
+ "line": {
1245
+ "color": "#2a3f5f"
1246
+ }
1247
+ },
1248
+ "ternary": {
1249
+ "aaxis": {
1250
+ "gridcolor": "white",
1251
+ "linecolor": "white",
1252
+ "ticks": ""
1253
+ },
1254
+ "baxis": {
1255
+ "gridcolor": "white",
1256
+ "linecolor": "white",
1257
+ "ticks": ""
1258
+ },
1259
+ "bgcolor": "#E5ECF6",
1260
+ "caxis": {
1261
+ "gridcolor": "white",
1262
+ "linecolor": "white",
1263
+ "ticks": ""
1264
+ }
1265
+ },
1266
+ "title": {
1267
+ "x": 0.05
1268
+ },
1269
+ "xaxis": {
1270
+ "automargin": true,
1271
+ "gridcolor": "white",
1272
+ "linecolor": "white",
1273
+ "ticks": "",
1274
+ "title": {
1275
+ "standoff": 15
1276
+ },
1277
+ "zerolinecolor": "white",
1278
+ "zerolinewidth": 2
1279
+ },
1280
+ "yaxis": {
1281
+ "automargin": true,
1282
+ "gridcolor": "white",
1283
+ "linecolor": "white",
1284
+ "ticks": "",
1285
+ "title": {
1286
+ "standoff": 15
1287
+ },
1288
+ "zerolinecolor": "white",
1289
+ "zerolinewidth": 2
1290
+ }
1291
+ }
1292
+ },
1293
+ "xaxis": {
1294
+ "anchor": "y",
1295
+ "domain": [
1296
+ 0,
1297
+ 1
1298
+ ],
1299
+ "title": {
1300
+ "text": "index"
1301
+ }
1302
+ },
1303
+ "yaxis": {
1304
+ "anchor": "x",
1305
+ "domain": [
1306
+ 0,
1307
+ 1
1308
+ ],
1309
+ "title": {
1310
+ "text": "value"
1311
+ }
1312
+ }
1313
+ }
1314
+ }
1315
+ },
1316
+ "metadata": {},
1317
+ "output_type": "display_data"
1318
+ }
1319
+ ],
1320
+ "source": [
1321
+ "px.line(df)"
1322
+ ]
1323
+ },
1324
  {
1325
  "cell_type": "code",
1326
  "execution_count": null,
impuestos.py CHANGED
@@ -1,4 +1,5 @@
1
  import pandas as pd
 
2
 
3
  # Valores de Junio 2022
4
  TRAMOS = {
@@ -59,3 +60,14 @@ def get_table(sueldo_bruto, tramos=TRAMOS):
59
  columns=["Desde", "Hasta", "Tasa", "Monto sujeto a impuesto", "Impuesto"],
60
  )
61
  return df
 
 
 
 
 
 
 
 
 
 
 
 
1
  import pandas as pd
2
+ import plotly.express as px
3
 
4
  # Valores de Junio 2022
5
  TRAMOS = {
 
60
  columns=["Desde", "Hasta", "Tasa", "Monto sujeto a impuesto", "Impuesto"],
61
  )
62
  return df
63
+
64
+
65
+ salarios = [450_000, 1000_000, 1_500_000, 2_000_000, 3_000_000, 5_000_000, 8_000_000, 10_000_000, 15_000_000]
66
+
67
+ def get_curve(descuentos):
68
+ def beneficios(s):
69
+ return max(s - descuentos, 0)
70
+ DF_CURVA = pd.DataFrame(columns=["actual", "reforma"], index=salarios)
71
+ DF_CURVA["actual"] = [sum(descomponer_en_tramos(s, TRAMOS)[1]) for s in salarios]
72
+ DF_CURVA["reforma"] = [sum(descomponer_en_tramos(beneficios(s) , TRAMOS_REFORMA)[1]) for s in salarios]
73
+ return px.line(DF_CURVA)