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datos001.ipynb
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"import pandas as pd\n",
"import numpy as np\n",
"import matplotlib.pyplot as plt\n",
"\n",
"#Cargamos los datos a nuestro notebook\n",
"df= pd.read_excel('/content/exceldemo.xlsx')"
],
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" Departamento Municipio Operadora \\\n",
"0 ANTIOQUIA PUERTO NARE ECOPETROL S.A. \n",
"1 ANTIOQUIA PUERTO NARE MANSAROVAR ENERGY COLOMBIA LTD \n",
"2 ANTIOQUIA PUERTO NARE MANSAROVAR ENERGY COLOMBIA LTD \n",
"3 ANTIOQUIA PUERTO TRIUNFO ECOPETROL S.A. \n",
"4 ANTIOQUIA YONDO ECOPETROL S.A. \n",
"\n",
" Contrato Campo Enero Febrero Marzo Abril \\\n",
"0 TECA COCORNA AREA TECA-COCORNA 1291.74 1285.10 1281.02 1254.71 \n",
"1 NARE NARE SUR 179.33 209.05 241.55 244.42 \n",
"2 NARE UNDERRIVER 798.30 745.97 736.98 673.28 \n",
"3 TECA COCORNA AREA TECA-COCORNA 205.95 213.24 199.52 183.49 \n",
"4 MAGDALENA MEDIO CASABE 10383.34 10307.74 10208.22 10161.94 \n",
"\n",
" Mayo Junio Julio Agosto Septiembre Octubre Noviembre \\\n",
"0 1323.26 1268.10 1198.19 1212.39 1356.37 1286.82 1546.81 \n",
"1 264.89 260.38 210.67 218.99 187.88 189.81 200.45 \n",
"2 664.03 1154.56 639.45 710.29 662.89 698.13 657.42 \n",
"3 164.47 164.93 150.85 125.04 131.28 122.17 140.35 \n",
"4 10251.03 10108.62 10636.26 9707.98 9795.50 10265.62 10958.90 \n",
"\n",
" Diciembre \n",
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"text": [
"<class 'pandas.core.frame.DataFrame'>\n",
"RangeIndex: 457 entries, 0 to 456\n",
"Data columns (total 17 columns):\n",
" # Column Non-Null Count Dtype \n",
"--- ------ -------------- ----- \n",
" 0 Departamento 456 non-null object \n",
" 1 Municipio 456 non-null object \n",
" 2 Operadora 456 non-null object \n",
" 3 Contrato 456 non-null object \n",
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" 11 Julio 457 non-null float64\n",
" 12 Agosto 457 non-null float64\n",
" 13 Septiembre 457 non-null float64\n",
" 14 Octubre 457 non-null float64\n",
" 15 Noviembre 457 non-null float64\n",
" 16 Diciembre 457 non-null float64\n",
"dtypes: float64(12), object(5)\n",
"memory usage: 60.8+ KB\n"
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"tdinamica = df.groupby([\"Departamento\"]).sum()"
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" Enero Febrero Marzo Abril Mayo \\\n",
"Departamento \n",
"ANTIOQUIA 15876.45 15748.86 15742.20 15656.03 15717.220 \n",
"ARAUCA 51716.52 54588.18 56523.85 57632.98 56797.160 \n",
"ATLANTICO 418.45 409.33 404.78 402.62 403.580 \n",
"BOLIVAR 11602.35 11926.20 12791.65 12308.90 14645.830 \n",
"BOYACA 33339.50 33241.34 31926.67 32395.65 32537.050 \n",
"CASANARE 176366.94 175290.65 170123.07 173311.35 173334.700 \n",
"CAUCA 569.21 543.70 534.68 529.31 537.880 \n",
"CESAR 25813.44 23897.92 24731.07 24212.54 22936.280 \n",
"CORDOBA 0.24 0.24 0.23 0.19 0.220 \n",
"CUNDINAMARCA 190.64 219.57 179.62 189.46 191.910 \n",
"DEPARTAMENTO NN 2780.23 2761.52 2647.46 2719.77 2921.300 \n",
"HUILA 23866.99 23691.76 23639.23 23020.07 23098.780 \n",
"MAGDALENA 162.33 155.60 156.68 151.44 134.450 \n",
"META 447518.28 444398.31 440003.54 442807.12 448726.367 \n",
"NARIÑO 263.29 260.03 256.08 258.76 16.700 \n",
"NORTE DE SANTANDER 2462.21 2525.93 2655.03 2776.03 2638.260 \n",
"PUTUMAYO 29566.70 29306.29 28776.01 29014.95 28916.320 \n",
"SANTANDER 62635.22 60579.24 60689.35 60273.14 57751.240 \n",
"SUCRE 36.51 39.62 34.87 35.43 36.670 \n",
"TOLIMA 13787.35 13105.15 13060.07 13315.69 13176.660 \n",
"\n",
" Junio Julio Agosto Septiembre \\\n",
"Departamento \n",
"ANTIOQUIA 15826.450000 15763.520000 13406.32 14572.69 \n",
"ARAUCA 59059.157000 44494.500000 59460.29 56718.64 \n",
"ATLANTICO 422.470000 520.480000 443.94 380.79 \n",
"BOLIVAR 16279.366667 16749.350000 16297.71 16573.82 \n",
"BOYACA 31619.910000 31716.510000 32241.57 31772.46 \n",
"CASANARE 172588.642667 169353.990000 167768.18 167027.37 \n",
"CAUCA 503.250000 452.800000 557.11 560.15 \n",
"CESAR 19533.860000 20026.884194 20436.50 20148.22 \n",
"CORDOBA 0.230000 0.250000 0.28 0.27 \n",
"CUNDINAMARCA 183.020000 188.590000 187.66 227.66 \n",
"DEPARTAMENTO NN 2814.220000 2221.090000 2626.62 2442.21 \n",
"HUILA 23350.880000 23602.870000 23743.29 24182.84 \n",
"MAGDALENA 145.780000 156.280000 154.01 149.59 \n",
"META 447187.240000 440212.750000 444958.77 442709.09 \n",
"NARIÑO 188.550000 259.140000 260.31 263.50 \n",
"NORTE DE SANTANDER 2639.020000 2129.710000 663.05 574.77 \n",
"PUTUMAYO 27355.020000 29126.670000 27681.46 28563.70 \n",
"SANTANDER 59538.355000 58933.270000 59329.68 60470.15 \n",
"SUCRE 32.110000 34.280000 33.45 34.49 \n",
"TOLIMA 12919.910000 12806.950000 12613.38 12125.01 \n",
"\n",
" Octubre Noviembre Diciembre \n",
"Departamento \n",
"ANTIOQUIA 15334.93 16403.71 17181.45 \n",
"ARAUCA 59744.84 57658.66 57142.34 \n",
"ATLANTICO 559.38 556.23 594.50 \n",
"BOLIVAR 14740.36 15703.73 16692.49 \n",
"BOYACA 31440.47 31162.03 30811.89 \n",
"CASANARE 165936.38 168036.60 164121.09 \n",
"CAUCA 518.92 618.29 680.73 \n",
"CESAR 19174.61 20326.83 19957.98 \n",
"CORDOBA 0.30 0.28 0.28 \n",
"CUNDINAMARCA 241.35 182.36 179.91 \n",
"DEPARTAMENTO NN 2395.88 2230.47 2012.74 \n",
"HUILA 23649.45 23597.95 23565.67 \n",
"MAGDALENA 147.03 140.43 136.74 \n",
"META 448103.60 443991.21 445548.82 \n",
"NARIÑO 257.81 260.16 260.09 \n",
"NORTE DE SANTANDER 689.62 1712.24 2208.49 \n",
"PUTUMAYO 29377.78 28314.21 30076.32 \n",
"SANTANDER 58798.86 57827.49 59392.47 \n",
"SUCRE 32.40 33.69 35.08 \n",
"TOLIMA 11604.82 11514.23 11623.23 "
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" </tr>\n",
" <tr>\n",
" <th>ATLANTICO</th>\n",
" <td>418.45</td>\n",
" <td>409.33</td>\n",
" <td>404.78</td>\n",
" <td>402.62</td>\n",
" <td>403.580</td>\n",
" <td>422.470000</td>\n",
" <td>520.480000</td>\n",
" <td>443.94</td>\n",
" <td>380.79</td>\n",
" <td>559.38</td>\n",
" <td>556.23</td>\n",
" <td>594.50</td>\n",
" </tr>\n",
" <tr>\n",
" <th>BOLIVAR</th>\n",
" <td>11602.35</td>\n",
" <td>11926.20</td>\n",
" <td>12791.65</td>\n",
" <td>12308.90</td>\n",
" <td>14645.830</td>\n",
" <td>16279.366667</td>\n",
" <td>16749.350000</td>\n",
" <td>16297.71</td>\n",
" <td>16573.82</td>\n",
" <td>14740.36</td>\n",
" <td>15703.73</td>\n",
" <td>16692.49</td>\n",
" </tr>\n",
" <tr>\n",
" <th>BOYACA</th>\n",
" <td>33339.50</td>\n",
" <td>33241.34</td>\n",
" <td>31926.67</td>\n",
" <td>32395.65</td>\n",
" <td>32537.050</td>\n",
" <td>31619.910000</td>\n",
" <td>31716.510000</td>\n",
" <td>32241.57</td>\n",
" <td>31772.46</td>\n",
" <td>31440.47</td>\n",
" <td>31162.03</td>\n",
" <td>30811.89</td>\n",
" </tr>\n",
" <tr>\n",
" <th>CASANARE</th>\n",
" <td>176366.94</td>\n",
" <td>175290.65</td>\n",
" <td>170123.07</td>\n",
" <td>173311.35</td>\n",
" <td>173334.700</td>\n",
" <td>172588.642667</td>\n",
" <td>169353.990000</td>\n",
" <td>167768.18</td>\n",
" <td>167027.37</td>\n",
" <td>165936.38</td>\n",
" <td>168036.60</td>\n",
" <td>164121.09</td>\n",
" </tr>\n",
" <tr>\n",
" <th>CAUCA</th>\n",
" <td>569.21</td>\n",
" <td>543.70</td>\n",
" <td>534.68</td>\n",
" <td>529.31</td>\n",
" <td>537.880</td>\n",
" <td>503.250000</td>\n",
" <td>452.800000</td>\n",
" <td>557.11</td>\n",
" <td>560.15</td>\n",
" <td>518.92</td>\n",
" <td>618.29</td>\n",
" <td>680.73</td>\n",
" </tr>\n",
" <tr>\n",
" <th>CESAR</th>\n",
" <td>25813.44</td>\n",
" <td>23897.92</td>\n",
" <td>24731.07</td>\n",
" <td>24212.54</td>\n",
" <td>22936.280</td>\n",
" <td>19533.860000</td>\n",
" <td>20026.884194</td>\n",
" <td>20436.50</td>\n",
" <td>20148.22</td>\n",
" <td>19174.61</td>\n",
" <td>20326.83</td>\n",
" <td>19957.98</td>\n",
" </tr>\n",
" <tr>\n",
" <th>CORDOBA</th>\n",
" <td>0.24</td>\n",
" <td>0.24</td>\n",
" <td>0.23</td>\n",
" <td>0.19</td>\n",
" <td>0.220</td>\n",
" <td>0.230000</td>\n",
" <td>0.250000</td>\n",
" <td>0.28</td>\n",
" <td>0.27</td>\n",
" <td>0.30</td>\n",
" <td>0.28</td>\n",
" <td>0.28</td>\n",
" </tr>\n",
" <tr>\n",
" <th>CUNDINAMARCA</th>\n",
" <td>190.64</td>\n",
" <td>219.57</td>\n",
" <td>179.62</td>\n",
" <td>189.46</td>\n",
" <td>191.910</td>\n",
" <td>183.020000</td>\n",
" <td>188.590000</td>\n",
" <td>187.66</td>\n",
" <td>227.66</td>\n",
" <td>241.35</td>\n",
" <td>182.36</td>\n",
" <td>179.91</td>\n",
" </tr>\n",
" <tr>\n",
" <th>DEPARTAMENTO NN</th>\n",
" <td>2780.23</td>\n",
" <td>2761.52</td>\n",
" <td>2647.46</td>\n",
" <td>2719.77</td>\n",
" <td>2921.300</td>\n",
" <td>2814.220000</td>\n",
" <td>2221.090000</td>\n",
" <td>2626.62</td>\n",
" <td>2442.21</td>\n",
" <td>2395.88</td>\n",
" <td>2230.47</td>\n",
" <td>2012.74</td>\n",
" </tr>\n",
" <tr>\n",
" <th>HUILA</th>\n",
" <td>23866.99</td>\n",
" <td>23691.76</td>\n",
" <td>23639.23</td>\n",
" <td>23020.07</td>\n",
" <td>23098.780</td>\n",
" <td>23350.880000</td>\n",
" <td>23602.870000</td>\n",
" <td>23743.29</td>\n",
" <td>24182.84</td>\n",
" <td>23649.45</td>\n",
" <td>23597.95</td>\n",
" <td>23565.67</td>\n",
" </tr>\n",
" <tr>\n",
" <th>MAGDALENA</th>\n",
" <td>162.33</td>\n",
" <td>155.60</td>\n",
" <td>156.68</td>\n",
" <td>151.44</td>\n",
" <td>134.450</td>\n",
" <td>145.780000</td>\n",
" <td>156.280000</td>\n",
" <td>154.01</td>\n",
" <td>149.59</td>\n",
" <td>147.03</td>\n",
" <td>140.43</td>\n",
" <td>136.74</td>\n",
" </tr>\n",
" <tr>\n",
" <th>META</th>\n",
" <td>447518.28</td>\n",
" <td>444398.31</td>\n",
" <td>440003.54</td>\n",
" <td>442807.12</td>\n",
" <td>448726.367</td>\n",
" <td>447187.240000</td>\n",
" <td>440212.750000</td>\n",
" <td>444958.77</td>\n",
" <td>442709.09</td>\n",
" <td>448103.60</td>\n",
" <td>443991.21</td>\n",
" <td>445548.82</td>\n",
" </tr>\n",
" <tr>\n",
" <th>NARIÑO</th>\n",
" <td>263.29</td>\n",
" <td>260.03</td>\n",
" <td>256.08</td>\n",
" <td>258.76</td>\n",
" <td>16.700</td>\n",
" <td>188.550000</td>\n",
" <td>259.140000</td>\n",
" <td>260.31</td>\n",
" <td>263.50</td>\n",
" <td>257.81</td>\n",
" <td>260.16</td>\n",
" <td>260.09</td>\n",
" </tr>\n",
" <tr>\n",
" <th>NORTE DE SANTANDER</th>\n",
" <td>2462.21</td>\n",
" <td>2525.93</td>\n",
" <td>2655.03</td>\n",
" <td>2776.03</td>\n",
" <td>2638.260</td>\n",
" <td>2639.020000</td>\n",
" <td>2129.710000</td>\n",
" <td>663.05</td>\n",
" <td>574.77</td>\n",
" <td>689.62</td>\n",
" <td>1712.24</td>\n",
" <td>2208.49</td>\n",
" </tr>\n",
" <tr>\n",
" <th>PUTUMAYO</th>\n",
" <td>29566.70</td>\n",
" <td>29306.29</td>\n",
" <td>28776.01</td>\n",
" <td>29014.95</td>\n",
" <td>28916.320</td>\n",
" <td>27355.020000</td>\n",
" <td>29126.670000</td>\n",
" <td>27681.46</td>\n",
" <td>28563.70</td>\n",
" <td>29377.78</td>\n",
" <td>28314.21</td>\n",
" <td>30076.32</td>\n",
" </tr>\n",
" <tr>\n",
" <th>SANTANDER</th>\n",
" <td>62635.22</td>\n",
" <td>60579.24</td>\n",
" <td>60689.35</td>\n",
" <td>60273.14</td>\n",
" <td>57751.240</td>\n",
" <td>59538.355000</td>\n",
" <td>58933.270000</td>\n",
" <td>59329.68</td>\n",
" <td>60470.15</td>\n",
" <td>58798.86</td>\n",
" <td>57827.49</td>\n",
" <td>59392.47</td>\n",
" </tr>\n",
" <tr>\n",
" <th>SUCRE</th>\n",
" <td>36.51</td>\n",
" <td>39.62</td>\n",
" <td>34.87</td>\n",
" <td>35.43</td>\n",
" <td>36.670</td>\n",
" <td>32.110000</td>\n",
" <td>34.280000</td>\n",
" <td>33.45</td>\n",
" <td>34.49</td>\n",
" <td>32.40</td>\n",
" <td>33.69</td>\n",
" <td>35.08</td>\n",
" </tr>\n",
" <tr>\n",
" <th>TOLIMA</th>\n",
" <td>13787.35</td>\n",
" <td>13105.15</td>\n",
" <td>13060.07</td>\n",
" <td>13315.69</td>\n",
" <td>13176.660</td>\n",
" <td>12919.910000</td>\n",
" <td>12806.950000</td>\n",
" <td>12613.38</td>\n",
" <td>12125.01</td>\n",
" <td>11604.82</td>\n",
" <td>11514.23</td>\n",
" <td>11623.23</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>\n",
" <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-f221c5fe-2fd0-4984-b106-dd737ad849d9')\"\n",
" title=\"Convert this dataframe to an interactive table.\"\n",
" style=\"display:none;\">\n",
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" </button>\n",
" \n",
" <style>\n",
" .colab-df-container {\n",
" display:flex;\n",
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" }\n",
"\n",
" .colab-df-convert {\n",
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" const docLinkHtml = 'Like what you see? Visit the ' +\n",
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]
},
"metadata": {},
"execution_count": 5
}
]
},
{
"cell_type": "code",
"source": [
"import random\n",
"def calculartrimestre(fila):\n",
" trimestral = fila[\"Enero\"] + fila[\"Febrero\"] + fila[\"Marzo\"]\n",
" return trimestral\n",
"\n",
"tdinamica[\"trimestral\"] = tdinamica.apply(calculartrimestre, axis=1)\n",
"\n",
"\n",
"def calcularcuatrimestral(fila):\n",
" cuatrimestral = fila[\"Enero\"] + fila[\"Febrero\"] + fila[\"Marzo\"] + fila[\"Abril\"]\n",
" return cuatrimestral\n",
"\n",
"tdinamica[\"cuatrimestra\"] = tdinamica.apply(calcularcuatrimestral, axis=1)\n",
"\n",
"def calcularsemestre(fila):\n",
" semestre = fila[\"Enero\"] + fila[\"Febrero\"] + fila[\"Marzo\"] + fila[\"Abril\"] + fila[\"Mayo\"] + fila[\"Junio\"]\n",
" return semestre\n",
"\n",
"tdinamica[\"semestre\"] = tdinamica.apply(calcularsemestre, axis=1)\n",
"\n",
"def calcularanual(fila):\n",
" anual = fila[\"Enero\"] + fila[\"Febrero\"] + fila[\"Marzo\"] + fila[\"Abril\"] + fila[\"Mayo\"] + fila[\"Junio\"] + fila[\"Julio\"] + fila[\"Agosto\"] + fila[\"Septiembre\"] + fila[\"Octubre\"] + fila[\"Noviembre\"] + fila[\"Diciembre\"]\n",
" return anual\n",
"\n",
"tdinamica[\"anual\"] = tdinamica.apply(calcularanual, axis=1)\n"
],
"metadata": {
"id": "kZ41wq1wst5i"
},
"execution_count": 11,
"outputs": []
},
{
"cell_type": "code",
"source": [
"tdinamica"
],
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/",
"height": 807
},
"id": "n076lKXHR-xd",
"outputId": "fcd299ee-01ed-4850-9fed-2e2066da6a53"
},
"execution_count": 15,
"outputs": [
{
"output_type": "execute_result",
"data": {
"text/plain": [
" Enero Febrero Marzo Abril Mayo \\\n",
"Departamento \n",
"ANTIOQUIA 15876.45 15748.86 15742.20 15656.03 15717.220 \n",
"ARAUCA 51716.52 54588.18 56523.85 57632.98 56797.160 \n",
"ATLANTICO 418.45 409.33 404.78 402.62 403.580 \n",
"BOLIVAR 11602.35 11926.20 12791.65 12308.90 14645.830 \n",
"BOYACA 33339.50 33241.34 31926.67 32395.65 32537.050 \n",
"CASANARE 176366.94 175290.65 170123.07 173311.35 173334.700 \n",
"CAUCA 569.21 543.70 534.68 529.31 537.880 \n",
"CESAR 25813.44 23897.92 24731.07 24212.54 22936.280 \n",
"CORDOBA 0.24 0.24 0.23 0.19 0.220 \n",
"CUNDINAMARCA 190.64 219.57 179.62 189.46 191.910 \n",
"DEPARTAMENTO NN 2780.23 2761.52 2647.46 2719.77 2921.300 \n",
"HUILA 23866.99 23691.76 23639.23 23020.07 23098.780 \n",
"MAGDALENA 162.33 155.60 156.68 151.44 134.450 \n",
"META 447518.28 444398.31 440003.54 442807.12 448726.367 \n",
"NARIÑO 263.29 260.03 256.08 258.76 16.700 \n",
"NORTE DE SANTANDER 2462.21 2525.93 2655.03 2776.03 2638.260 \n",
"PUTUMAYO 29566.70 29306.29 28776.01 29014.95 28916.320 \n",
"SANTANDER 62635.22 60579.24 60689.35 60273.14 57751.240 \n",
"SUCRE 36.51 39.62 34.87 35.43 36.670 \n",
"TOLIMA 13787.35 13105.15 13060.07 13315.69 13176.660 \n",
"\n",
" Junio Julio Agosto Septiembre \\\n",
"Departamento \n",
"ANTIOQUIA 15826.450000 15763.520000 13406.32 14572.69 \n",
"ARAUCA 59059.157000 44494.500000 59460.29 56718.64 \n",
"ATLANTICO 422.470000 520.480000 443.94 380.79 \n",
"BOLIVAR 16279.366667 16749.350000 16297.71 16573.82 \n",
"BOYACA 31619.910000 31716.510000 32241.57 31772.46 \n",
"CASANARE 172588.642667 169353.990000 167768.18 167027.37 \n",
"CAUCA 503.250000 452.800000 557.11 560.15 \n",
"CESAR 19533.860000 20026.884194 20436.50 20148.22 \n",
"CORDOBA 0.230000 0.250000 0.28 0.27 \n",
"CUNDINAMARCA 183.020000 188.590000 187.66 227.66 \n",
"DEPARTAMENTO NN 2814.220000 2221.090000 2626.62 2442.21 \n",
"HUILA 23350.880000 23602.870000 23743.29 24182.84 \n",
"MAGDALENA 145.780000 156.280000 154.01 149.59 \n",
"META 447187.240000 440212.750000 444958.77 442709.09 \n",
"NARIÑO 188.550000 259.140000 260.31 263.50 \n",
"NORTE DE SANTANDER 2639.020000 2129.710000 663.05 574.77 \n",
"PUTUMAYO 27355.020000 29126.670000 27681.46 28563.70 \n",
"SANTANDER 59538.355000 58933.270000 59329.68 60470.15 \n",
"SUCRE 32.110000 34.280000 33.45 34.49 \n",
"TOLIMA 12919.910000 12806.950000 12613.38 12125.01 \n",
"\n",
" Octubre Noviembre Diciembre trimestral cuatrimestra \\\n",
"Departamento \n",
"ANTIOQUIA 15334.93 16403.71 17181.45 47367.51 63023.54 \n",
"ARAUCA 59744.84 57658.66 57142.34 162828.55 220461.53 \n",
"ATLANTICO 559.38 556.23 594.50 1232.56 1635.18 \n",
"BOLIVAR 14740.36 15703.73 16692.49 36320.20 48629.10 \n",
"BOYACA 31440.47 31162.03 30811.89 98507.51 130903.16 \n",
"CASANARE 165936.38 168036.60 164121.09 521780.66 695092.01 \n",
"CAUCA 518.92 618.29 680.73 1647.59 2176.90 \n",
"CESAR 19174.61 20326.83 19957.98 74442.43 98654.97 \n",
"CORDOBA 0.30 0.28 0.28 0.71 0.90 \n",
"CUNDINAMARCA 241.35 182.36 179.91 589.83 779.29 \n",
"DEPARTAMENTO NN 2395.88 2230.47 2012.74 8189.21 10908.98 \n",
"HUILA 23649.45 23597.95 23565.67 71197.98 94218.05 \n",
"MAGDALENA 147.03 140.43 136.74 474.61 626.05 \n",
"META 448103.60 443991.21 445548.82 1331920.13 1774727.25 \n",
"NARIÑO 257.81 260.16 260.09 779.40 1038.16 \n",
"NORTE DE SANTANDER 689.62 1712.24 2208.49 7643.17 10419.20 \n",
"PUTUMAYO 29377.78 28314.21 30076.32 87649.00 116663.95 \n",
"SANTANDER 58798.86 57827.49 59392.47 183903.81 244176.95 \n",
"SUCRE 32.40 33.69 35.08 111.00 146.43 \n",
"TOLIMA 11604.82 11514.23 11623.23 39952.57 53268.26 \n",
"\n",
" semestre anual \n",
"Departamento \n",
"ANTIOQUIA 9.456721e+04 1.872298e+05 \n",
"ARAUCA 3.363178e+05 6.715371e+05 \n",
"ATLANTICO 2.461230e+03 5.516550e+03 \n",
"BOLIVAR 7.955430e+04 1.763118e+05 \n",
"BOYACA 1.950601e+05 3.842051e+05 \n",
"CASANARE 1.041015e+06 2.043259e+06 \n",
"CAUCA 3.218030e+03 6.606030e+03 \n",
"CESAR 1.411251e+05 2.611961e+05 \n",
"CORDOBA 1.350000e+00 3.010000e+00 \n",
"CUNDINAMARCA 1.154220e+03 2.361750e+03 \n",
"DEPARTAMENTO NN 1.664450e+04 3.057351e+04 \n",
"HUILA 1.406677e+05 2.830098e+05 \n",
"MAGDALENA 9.062800e+02 1.790360e+03 \n",
"META 2.670641e+06 5.336165e+06 \n",
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"NORTE DE SANTANDER 1.569648e+04 2.367436e+04 \n",
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" <td>594.50</td>\n",
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" <td>14645.830</td>\n",
" <td>16279.366667</td>\n",
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" <td>16297.71</td>\n",
" <td>16573.82</td>\n",
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" <td>16692.49</td>\n",
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" <td>183.020000</td>\n",
" <td>188.590000</td>\n",
" <td>187.66</td>\n",
" <td>227.66</td>\n",
" <td>241.35</td>\n",
" <td>182.36</td>\n",
" <td>179.91</td>\n",
" <td>589.83</td>\n",
" <td>779.29</td>\n",
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" <td>23098.780</td>\n",
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" <td>23602.870000</td>\n",
" <td>23743.29</td>\n",
" <td>24182.84</td>\n",
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" <td>23597.95</td>\n",
" <td>23565.67</td>\n",
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" <td>154.01</td>\n",
" <td>149.59</td>\n",
" <td>147.03</td>\n",
" <td>140.43</td>\n",
" <td>136.74</td>\n",
" <td>474.61</td>\n",
" <td>626.05</td>\n",
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" <td>443991.21</td>\n",
" <td>445548.82</td>\n",
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" <td>188.550000</td>\n",
" <td>259.140000</td>\n",
" <td>260.31</td>\n",
" <td>263.50</td>\n",
" <td>257.81</td>\n",
" <td>260.16</td>\n",
" <td>260.09</td>\n",
" <td>779.40</td>\n",
" <td>1038.16</td>\n",
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" <td>2638.260</td>\n",
" <td>2639.020000</td>\n",
" <td>2129.710000</td>\n",
" <td>663.05</td>\n",
" <td>574.77</td>\n",
" <td>689.62</td>\n",
" <td>1712.24</td>\n",
" <td>2208.49</td>\n",
" <td>7643.17</td>\n",
" <td>10419.20</td>\n",
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" <td>28916.320</td>\n",
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" <td>29126.670000</td>\n",
" <td>27681.46</td>\n",
" <td>28563.70</td>\n",
" <td>29377.78</td>\n",
" <td>28314.21</td>\n",
" <td>30076.32</td>\n",
" <td>87649.00</td>\n",
" <td>116663.95</td>\n",
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" <td>60273.14</td>\n",
" <td>57751.240</td>\n",
" <td>59538.355000</td>\n",
" <td>58933.270000</td>\n",
" <td>59329.68</td>\n",
" <td>60470.15</td>\n",
" <td>58798.86</td>\n",
" <td>57827.49</td>\n",
" <td>59392.47</td>\n",
" <td>183903.81</td>\n",
" <td>244176.95</td>\n",
" <td>3.614665e+05</td>\n",
" <td>7.162185e+05</td>\n",
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" <th>SUCRE</th>\n",
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" <td>39.62</td>\n",
" <td>34.87</td>\n",
" <td>35.43</td>\n",
" <td>36.670</td>\n",
" <td>32.110000</td>\n",
" <td>34.280000</td>\n",
" <td>33.45</td>\n",
" <td>34.49</td>\n",
" <td>32.40</td>\n",
" <td>33.69</td>\n",
" <td>35.08</td>\n",
" <td>111.00</td>\n",
" <td>146.43</td>\n",
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" <td>13315.69</td>\n",
" <td>13176.660</td>\n",
" <td>12919.910000</td>\n",
" <td>12806.950000</td>\n",
" <td>12613.38</td>\n",
" <td>12125.01</td>\n",
" <td>11604.82</td>\n",
" <td>11514.23</td>\n",
" <td>11623.23</td>\n",
" <td>39952.57</td>\n",
" <td>53268.26</td>\n",
" <td>7.936483e+04</td>\n",
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]
},
"metadata": {},
"execution_count": 15
}
]
},
{
"cell_type": "code",
"source": [
"tproduccion = tdinamica[[\"trimestral\",\"cuatrimestra\",\"semestre\",\"anual\"]]"
],
"metadata": {
"id": "e0-Fe6lTnN-Q"
},
"execution_count": 16,
"outputs": []
},
{
"cell_type": "code",
"source": [
"tproduccion"
],
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/",
"height": 708
},
"id": "7LxW1C81nWS6",
"outputId": "347a6348-cc7c-4007-8290-d9bf681022a9"
},
"execution_count": 17,
"outputs": [
{
"output_type": "execute_result",
"data": {
"text/plain": [
" trimestral cuatrimestra semestre anual\n",
"Departamento \n",
"ANTIOQUIA 47367.51 63023.54 9.456721e+04 1.872298e+05\n",
"ARAUCA 162828.55 220461.53 3.363178e+05 6.715371e+05\n",
"ATLANTICO 1232.56 1635.18 2.461230e+03 5.516550e+03\n",
"BOLIVAR 36320.20 48629.10 7.955430e+04 1.763118e+05\n",
"BOYACA 98507.51 130903.16 1.950601e+05 3.842051e+05\n",
"CASANARE 521780.66 695092.01 1.041015e+06 2.043259e+06\n",
"CAUCA 1647.59 2176.90 3.218030e+03 6.606030e+03\n",
"CESAR 74442.43 98654.97 1.411251e+05 2.611961e+05\n",
"CORDOBA 0.71 0.90 1.350000e+00 3.010000e+00\n",
"CUNDINAMARCA 589.83 779.29 1.154220e+03 2.361750e+03\n",
"DEPARTAMENTO NN 8189.21 10908.98 1.664450e+04 3.057351e+04\n",
"HUILA 71197.98 94218.05 1.406677e+05 2.830098e+05\n",
"MAGDALENA 474.61 626.05 9.062800e+02 1.790360e+03\n",
"META 1331920.13 1774727.25 2.670641e+06 5.336165e+06\n",
"NARIÑO 779.40 1038.16 1.243410e+03 2.804420e+03\n",
"NORTE DE SANTANDER 7643.17 10419.20 1.569648e+04 2.367436e+04\n",
"PUTUMAYO 87649.00 116663.95 1.729353e+05 3.460754e+05\n",
"SANTANDER 183903.81 244176.95 3.614665e+05 7.162185e+05\n",
"SUCRE 111.00 146.43 2.152100e+02 4.186000e+02\n",
"TOLIMA 39952.57 53268.26 7.936483e+04 1.516525e+05"
],
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"metadata": {},
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},
{
"cell_type": "code",
"source": [
"cincoprimeros = tproduccion.sort_values(by=[\"trimestral\",\"Departamento\"], ascending=[False,True])\n",
"cincoprimeros.head()"
],
"metadata": {
"colab": {
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"id": "2Fbd11jie-x7",
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"execution_count": 33,
"outputs": [
{
"output_type": "execute_result",
"data": {
"text/plain": [
" trimestral cuatrimestra semestre anual\n",
"Departamento \n",
"META 1331920.13 1774727.25 2.670641e+06 5.336165e+06\n",
"CASANARE 521780.66 695092.01 1.041015e+06 2.043259e+06\n",
"SANTANDER 183903.81 244176.95 3.614665e+05 7.162185e+05\n",
"ARAUCA 162828.55 220461.53 3.363178e+05 6.715371e+05\n",
"BOYACA 98507.51 130903.16 1.950601e+05 3.842051e+05"
],
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"\n",
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" '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
" + ' to learn more about interactive tables.';\n",
" element.innerHTML = '';\n",
" dataTable['output_type'] = 'display_data';\n",
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" docLink.innerHTML = docLinkHtml;\n",
" element.appendChild(docLink);\n",
" }\n",
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]
},
"metadata": {},
"execution_count": 33
}
]
},
{
"cell_type": "code",
"source": [
"cincoprimeros.plot(kind = \"bar\")\n",
"plt.show()"
],
"metadata": {
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"height": 395
},
"id": "yrZSO42mSQvC",
"outputId": "168d9e85-02db-4a09-a86b-d02e652d82ae"
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"outputs": [
{
"output_type": "display_data",
"data": {
"text/plain": [
"<Figure size 432x288 with 1 Axes>"
],
"image/png": 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\n"
},
"metadata": {
"needs_background": "light"
}
}
]
},
{
"cell_type": "code",
"source": [
"cincoprimeros.plot(kind = \"line\")\n",
"plt.show()"
],
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/",
"height": 290
},
"id": "dbsRe28HuSX-",
"outputId": "e5f5469f-bef2-4229-b1d1-f3ddf935ea50"
},
"execution_count": 35,
"outputs": [
{
"output_type": "display_data",
"data": {
"text/plain": [
"<Figure size 432x288 with 1 Axes>"
],
"image/png": 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\n"
},
"metadata": {
"needs_background": "light"
}
}
]
},
{
"cell_type": "code",
"source": [
"cincoprimeros.plot(kind = \"barh\")\n",
"plt.show()"
],
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/",
"height": 278
},
"id": "tlTCoFw4uqV7",
"outputId": "3de1e5a2-2ccb-4d11-9030-95f34bb19e15"
},
"execution_count": 38,
"outputs": [
{
"output_type": "display_data",
"data": {
"text/plain": [
"<Figure size 432x288 with 1 Axes>"
],
"image/png": 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\n"
},
"metadata": {
"needs_background": "light"
}
}
]
}
]
}
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