{ "cells": [ { "cell_type": "code", "execution_count": 1, "metadata": { "ExecuteTime": { "end_time": "2018-12-16T15:52:23.140521Z", "start_time": "2018-12-16T15:52:19.063112Z" } }, "outputs": [], "source": [ "import pandas as pd, numpy as np, requests" ] }, { "cell_type": "code", "execution_count": 5, "metadata": { "ExecuteTime": { "end_time": "2018-12-16T15:55:29.347841Z", "start_time": "2018-12-16T15:55:28.598841Z" } }, "outputs": [], "source": [ "%matplotlib inline\n", "import matplotlib.pyplot as plt\n", "from matplotlib.patches import Rectangle\n", "import mpld3\n", "mpld3.enable_notebook()" ] }, { "cell_type": "code", "execution_count": 9, "metadata": { "ExecuteTime": { "end_time": "2018-12-16T19:47:05.807561Z", "start_time": "2018-12-16T19:47:05.268560Z" } }, "outputs": [], "source": [ "data3=pd.read_excel('export3.xlsx')" ] }, { "cell_type": "code", "execution_count": 11, "metadata": { "ExecuteTime": { "end_time": "2018-12-16T19:47:36.637236Z", "start_time": "2018-12-16T19:47:36.478232Z" } }, "outputs": [ { "data": { "text/html": [ "
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20142015201620172014.12015.12016.12017.12014.22015.22016.22017.22014.32015.32016.32017.3RégióHosszúságSzélességIparág
A M C SRLNaNNaNNaNNaN18131027.022173039.024390005.027881270.018.13122.17324.39027.881NaNNaNNaNNaNAlsó-háromszék25.58921645.839135Kereskedelem
ABC IMPEX SRL120.0132.0132.0145.030363973.031956498.033071733.036539530.030.36431.95633.07236.5400.2530.2420.2510.252Udvarhelyszék25.29003446.289768Kisipar, műanyag
ABRAZIV SRLNaNNaNNaNNaN0.00.00.05483275.00.0000.0000.0005.483NaNNaNNaNNaNGyergyószék25.57516546.717425Kereskedelem
ADIMAG COM IMPEX SRLNaNNaNNaNNaN44031925.047437389.048827471.057106224.044.03247.43748.82757.106NaNNaNNaNNaNMarosszék24.54881946.537905Építkezés
AFEROM TRANS SRLNaNNaNNaNNaN12096492.012531454.013592056.013341348.012.09612.53113.59213.341NaNNaNNaNNaNCsíkszék25.78607146.361412Szállítás
AGER SRLNaNNaNNaNNaN10322534.010511810.010629185.014549472.010.32310.51210.62914.549NaNNaNNaNNaNAlsó-háromszék26.02914245.667196Kisipar, műanyag
AGM ECO CORPORATE SRL6.02.036.068.0NaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNUdvarhelyszék25.31172946.316023Élelmiszer
AGRICO M SRLNaNNaNNaNNaN5701521.06376915.07643351.09400301.05.7026.3777.6439.400NaNNaNNaNNaNFelső-háromszék26.13267046.006632Mezőgazdaság
AGRO PAN STAR SRLNaNNaNNaNNaN2845996.013372911.020905425.019033775.02.84613.37320.90519.034NaNNaNNaNNaNAlsó-háromszék25.79325845.870001Élelmiszer
AGRO ROM IMPEX SRLNaNNaNNaNNaN21671970.029093421.043731414.052824141.021.67229.09343.73152.824NaNNaNNaNNaNMarosszék24.53183946.526013Kereskedelem
AGROPROD CARTOF SRLNaNNaNNaNNaN695186.06257500.09738941.06144223.00.6956.2589.7396.144NaNNaNNaNNaNFelső-háromszék26.13771145.993911Mezőgazdaság
AGROWEST BMB SRLNaNNaNNaNNaN11025678.09992347.010107975.010271662.011.0269.99210.10810.272NaNNaNNaNNaNFelső-háromszék26.03492745.959291Mezőgazdaság
AIRQUEE SRL123.0161.0192.0194.012506711.017489284.019580909.020263081.012.50717.48919.58120.2630.1020.1090.1020.104Alsó-háromszék25.81394845.863252Kereskedelem
ALEX & CO SA173.0174.0144.0143.013850999.015773075.015610215.016942918.013.85115.77315.61016.9430.0800.0910.1080.118Alsó-háromszék25.80431945.773468Fa, bútor
ALIAT AUTO SRLNaNNaNNaNNaN60851171.069603591.091134374.0104993558.060.85169.60491.134104.994NaNNaNNaNNaNMarosszék24.54035246.526409Kereskedelem
ALLCOLORS SERV SRL126.0154.0172.0228.0NaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNMarosszék24.41634346.471794Szolgáltatás
ALMI ROM SRLNaNNaNNaNNaN11362558.012418359.014487619.018494022.011.36312.41814.48818.494NaNNaNNaNNaNGyergyószék25.57557846.714488Élelmiszer
ALT TECHNOLOGIES TRANSYLVANIA SRL156.0176.0186.0198.037934554.053072027.054277063.054588122.037.93553.07254.27754.5880.2430.3020.2920.276Udvarhelyszék25.21667246.385158Kisipar, műanyag
ALUTUS SA51.041.051.047.0NaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNCsíkszék25.77230946.369458Kisipar, műanyag
ALZOCOM-TRANSPORT SRLNaNNaNNaNNaN10426539.012785106.013720358.016841974.010.42712.78513.72016.842NaNNaNNaNNaNCsíkszék25.80729746.356965Szállítás
AMECO RENEWABLE ENERGY SRL83.059.030.034.021180409.019744193.07623894.011285020.021.18019.7447.62411.2850.2550.3350.2540.332Gyergyószék25.57454146.718254Fa, bútor
AMIGO & INTERCOST SRL631.0620.0724.0786.0276276037.0290602580.0338871404.0381852182.0276.276290.603338.871381.8520.4380.4690.4680.486Udvarhelyszék25.30451846.314643Kereskedelem
AMIGO SRLNaNNaNNaNNaN17290545.019643902.022490359.028169310.017.29119.64422.49028.169NaNNaNNaNNaNCsíkszék25.79037346.359746Kereskedelem
APC UNIVERSAL PARTNER SRLNaNNaN1.0139.0NaNNaN0.017535928.0NaNNaN0.00017.536NaNNaN0.0000.126Udvarhelyszék25.31335646.316934Kereskedelem
APEMIN TUSNAD SA145.0137.0136.0143.037154570.041361947.045394719.051210314.037.15541.36245.39551.2100.2560.3020.3340.358Csíkszék25.91194846.206866Ásványvíz
AQUA CALIMANI SRL40.037.035.034.0NaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNGyergyószék25.35080246.922981Ásványvíz
AQUA NOVA HARGITA SRL110.0110.0109.0108.0NaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNUdvarhelyszék25.30956146.314822Szolgáltatás
ARAMIS RO SRL151.0143.0141.0152.0NaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNUdvarhelyszék25.30612746.311619Szolgáltatás
ARCON SRL161.0159.0151.0101.0120246976.0124968490.0110394138.083022166.0120.247124.968110.39483.0220.7470.7860.7310.822Alsó-háromszék25.78927945.868490Kisipar, műanyag
ARTEMOB INTERNATIONAL SRL512.0508.0511.0579.062058764.064999036.096337149.0134053580.062.05964.99996.337134.0540.1210.1280.1890.232Marosszék25.07501046.575623Fa, bútor
...............................................................
TRICOMSERV SA87.087.087.075.016389103.017599455.015453556.011980197.016.38917.59915.45411.9800.1880.2020.1780.160Alsó-háromszék25.78664445.855076Kisipar, műanyag
TRIMEX SERVICII SRLNaNNaNNaNNaN8239848.010185155.013535129.08928863.08.24010.18513.5358.929NaNNaNNaNNaNFelső-háromszék26.06374646.040239Építkezés
TRIO IMPEX SRL66.074.081.072.0NaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNAlsó-háromszék25.85000045.950000Szállítás
TROPICAL SRLNaNNaNNaNNaN8511397.07113164.06656268.07698693.08.5117.1136.6567.699NaNNaNNaNNaNGyergyószék25.50000046.700000Szállítás
TURISM COVASNA SA84.083.099.0105.010079313.09665694.011254632.012120757.010.0799.66611.25512.1210.1200.1160.1140.115Felső-háromszék26.16681645.844993Vendéglátó
TUSNAD SA91.093.094.094.0NaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNCsíkszék25.86056346.146941Vendéglátó
UDVARHELYI HIRADO SRL271.0281.0299.0195.0NaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNUdvarhelyszék25.30256546.300650Szolgáltatás
UNIC TRIO SRL54.055.056.054.0NaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNCsíkszék25.80639346.655610Élelmiszer
UNIO LUNCA SRL68.072.070.074.0NaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNCsíkszék25.95412346.559288Élelmiszer
UNIPREST INSTAL SRLNaNNaNNaNNaN65084212.081287908.092938901.0111860492.065.08481.28892.939111.860NaNNaNNaNNaNMarosszék24.53183946.526013Szolgáltatás
UPS DISTRIBUTION SRLNaNNaNNaNNaN8549844.08323927.08901784.09939657.08.5508.3248.9029.940NaNNaNNaNNaNGyergyószék25.60235346.715585Szolgáltatás
VALDEK IMPEX SRL178.0155.0130.0121.064206026.098072334.038466262.022250435.064.20698.07238.46622.2500.3610.6330.2960.184Alsó-háromszék25.78934045.865936Építkezés
VALKES SRL1416.01007.0886.0788.036661502.031885928.032843165.030626442.036.66231.88632.84330.6260.0260.0320.0370.039Alsó-háromszék25.80665145.855129Kisipar, műanyag
VBH ROMCOM SRLNaNNaNNaNNaN39811744.046612739.049332868.054520221.039.81246.61349.33354.520NaNNaNNaNNaNMarosszék24.54035246.526409Kisipar, műanyag
VEL FUNGO SRLNaNNaNNaNNaN7089148.08315513.014907258.026121250.07.0898.31614.90726.121NaNNaNNaNNaNCsíkszék25.75315246.437482Mezőgazdaság
VIADUCT SRL109.0135.0157.0151.027305770.030606802.026571799.023616230.027.30630.60726.57223.6160.2510.2270.1690.156Udvarhelyszék25.32077746.322821Építkezés
VIASTEIN SRLNaNNaNNaNNaN12024620.015236830.015295661.017168209.012.02515.23715.29617.168NaNNaNNaNNaNAlsó-háromszék25.79971645.770781Építkezés
VIASTRADA SRL19.023.027.034.08452400.07945073.09049705.012107718.08.4527.9459.05012.1080.4450.3450.3350.356Gyergyószék25.59812346.696028Szállítás
VIKING SRL72.094.094.094.0NaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNUdvarhelyszék25.29397646.307330Építkezés
VILLEX SRL19.021.023.028.0NaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNFelső-háromszék26.13505845.999479Kereskedelem
WABERER S ROMANIA SA159.073.070.070.070231898.045080527.039478024.030033637.070.23245.08139.47830.0340.4420.6180.5640.429Csíkszék25.74845746.370803Szállítás
WALOR RO SRL157.0163.0176.0215.048459276.057782546.079335550.0103680748.048.45957.78379.336103.6810.3090.3540.4510.482Alsó-háromszék25.81851545.861235Kisipar, műanyag
WEEKEND SRLNaNNaNNaNNaN14800679.015555277.020504368.019455456.014.80115.55520.50419.455NaNNaNNaNNaNAlsó-háromszék25.79579145.865823Kereskedelem
WERNETTO SRL45.045.062.051.01813259.01813259.06602913.012704346.01.8131.8136.60312.7040.0400.0400.1060.249Gyergyószék25.58552746.721211Építkezés
WIKEND FOREST IMPEX SRLNaNNaNNaNNaN5227975.07843382.07195045.06952665.05.2287.8437.1956.953NaNNaNNaNNaNGyergyószék25.44265846.796304Építkezés
WONDERLAND SRL27.029.028.029.0NaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNFelső-háromszék26.06374646.040239Építkezés
ZABOLA ESTATE SRL20.023.025.031.0NaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNFelső-háromszék26.19802945.891556Vendéglátó
ZAMBELLI METAL SRL136.0163.0162.0179.028480483.027891895.034591562.042016920.028.48027.89234.59242.0170.2090.1710.2140.235Alsó-háromszék25.81851545.861235Szolgáltatás
ZARAH MODEN SRL826.0839.0778.0785.0144887360.0139752712.0141121629.0148531005.0144.887139.753141.122148.5310.1750.1670.1810.189Felső-háromszék26.13596745.996939Textil
ZENCO TRANS SRL30.033.033.037.0NaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNGyergyószék25.35340446.926030Szállítás
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424 rows × 20 columns

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" ], "text/plain": [ " 2014 2015 2016 2017 2014.1 \\\n", "A M C SRL NaN NaN NaN NaN 18131027.0 \n", "ABC IMPEX SRL 120.0 132.0 132.0 145.0 30363973.0 \n", "ABRAZIV SRL NaN NaN NaN NaN 0.0 \n", "ADIMAG COM IMPEX SRL NaN NaN NaN NaN 44031925.0 \n", "AFEROM TRANS SRL NaN NaN NaN NaN 12096492.0 \n", "AGER SRL NaN NaN NaN NaN 10322534.0 \n", "AGM ECO CORPORATE SRL 6.0 2.0 36.0 68.0 NaN \n", "AGRICO M SRL NaN NaN NaN NaN 5701521.0 \n", "AGRO PAN STAR SRL NaN NaN NaN NaN 2845996.0 \n", "AGRO ROM IMPEX SRL NaN NaN NaN NaN 21671970.0 \n", "AGROPROD CARTOF SRL NaN NaN NaN NaN 695186.0 \n", "AGROWEST BMB SRL NaN NaN NaN NaN 11025678.0 \n", "AIRQUEE SRL 123.0 161.0 192.0 194.0 12506711.0 \n", "ALEX & CO SA 173.0 174.0 144.0 143.0 13850999.0 \n", "ALIAT AUTO SRL NaN NaN NaN NaN 60851171.0 \n", "ALLCOLORS SERV SRL 126.0 154.0 172.0 228.0 NaN \n", "ALMI ROM SRL NaN NaN NaN NaN 11362558.0 \n", "ALT TECHNOLOGIES TRANSYLVANIA SRL 156.0 176.0 186.0 198.0 37934554.0 \n", "ALUTUS SA 51.0 41.0 51.0 47.0 NaN \n", "ALZOCOM-TRANSPORT SRL NaN NaN NaN NaN 10426539.0 \n", "AMECO RENEWABLE ENERGY SRL 83.0 59.0 30.0 34.0 21180409.0 \n", "AMIGO & INTERCOST SRL 631.0 620.0 724.0 786.0 276276037.0 \n", "AMIGO SRL NaN NaN NaN NaN 17290545.0 \n", "APC UNIVERSAL PARTNER SRL NaN NaN 1.0 139.0 NaN \n", "APEMIN TUSNAD SA 145.0 137.0 136.0 143.0 37154570.0 \n", "AQUA CALIMANI SRL 40.0 37.0 35.0 34.0 NaN \n", "AQUA NOVA HARGITA SRL 110.0 110.0 109.0 108.0 NaN \n", "ARAMIS RO SRL 151.0 143.0 141.0 152.0 NaN \n", "ARCON SRL 161.0 159.0 151.0 101.0 120246976.0 \n", "ARTEMOB INTERNATIONAL SRL 512.0 508.0 511.0 579.0 62058764.0 \n", "... ... ... ... ... ... \n", "TRICOMSERV SA 87.0 87.0 87.0 75.0 16389103.0 \n", "TRIMEX SERVICII SRL NaN NaN NaN NaN 8239848.0 \n", "TRIO IMPEX SRL 66.0 74.0 81.0 72.0 NaN \n", "TROPICAL SRL NaN NaN NaN NaN 8511397.0 \n", "TURISM COVASNA SA 84.0 83.0 99.0 105.0 10079313.0 \n", "TUSNAD SA 91.0 93.0 94.0 94.0 NaN \n", "UDVARHELYI HIRADO SRL 271.0 281.0 299.0 195.0 NaN \n", "UNIC TRIO SRL 54.0 55.0 56.0 54.0 NaN \n", "UNIO LUNCA SRL 68.0 72.0 70.0 74.0 NaN \n", "UNIPREST INSTAL SRL NaN NaN NaN NaN 65084212.0 \n", "UPS DISTRIBUTION SRL NaN NaN NaN NaN 8549844.0 \n", "VALDEK IMPEX SRL 178.0 155.0 130.0 121.0 64206026.0 \n", "VALKES SRL 1416.0 1007.0 886.0 788.0 36661502.0 \n", "VBH ROMCOM SRL NaN NaN NaN NaN 39811744.0 \n", "VEL FUNGO SRL NaN NaN NaN NaN 7089148.0 \n", "VIADUCT SRL 109.0 135.0 157.0 151.0 27305770.0 \n", "VIASTEIN SRL NaN NaN NaN NaN 12024620.0 \n", "VIASTRADA SRL 19.0 23.0 27.0 34.0 8452400.0 \n", "VIKING SRL 72.0 94.0 94.0 94.0 NaN \n", "VILLEX SRL 19.0 21.0 23.0 28.0 NaN \n", "WABERER S ROMANIA SA 159.0 73.0 70.0 70.0 70231898.0 \n", "WALOR RO SRL 157.0 163.0 176.0 215.0 48459276.0 \n", "WEEKEND SRL NaN NaN NaN NaN 14800679.0 \n", "WERNETTO SRL 45.0 45.0 62.0 51.0 1813259.0 \n", "WIKEND FOREST IMPEX SRL NaN NaN NaN NaN 5227975.0 \n", "WONDERLAND SRL 27.0 29.0 28.0 29.0 NaN \n", "ZABOLA ESTATE SRL 20.0 23.0 25.0 31.0 NaN \n", "ZAMBELLI METAL SRL 136.0 163.0 162.0 179.0 28480483.0 \n", "ZARAH MODEN SRL 826.0 839.0 778.0 785.0 144887360.0 \n", "ZENCO TRANS SRL 30.0 33.0 33.0 37.0 NaN \n", "\n", " 2015.1 2016.1 2017.1 \\\n", "A M C SRL 22173039.0 24390005.0 27881270.0 \n", "ABC IMPEX SRL 31956498.0 33071733.0 36539530.0 \n", "ABRAZIV SRL 0.0 0.0 5483275.0 \n", "ADIMAG COM IMPEX SRL 47437389.0 48827471.0 57106224.0 \n", "AFEROM TRANS SRL 12531454.0 13592056.0 13341348.0 \n", "AGER SRL 10511810.0 10629185.0 14549472.0 \n", "AGM ECO CORPORATE SRL NaN NaN NaN \n", "AGRICO M SRL 6376915.0 7643351.0 9400301.0 \n", "AGRO PAN STAR SRL 13372911.0 20905425.0 19033775.0 \n", "AGRO ROM IMPEX SRL 29093421.0 43731414.0 52824141.0 \n", "AGROPROD CARTOF SRL 6257500.0 9738941.0 6144223.0 \n", "AGROWEST BMB SRL 9992347.0 10107975.0 10271662.0 \n", "AIRQUEE SRL 17489284.0 19580909.0 20263081.0 \n", "ALEX & CO SA 15773075.0 15610215.0 16942918.0 \n", "ALIAT AUTO SRL 69603591.0 91134374.0 104993558.0 \n", "ALLCOLORS SERV SRL NaN NaN NaN \n", "ALMI ROM SRL 12418359.0 14487619.0 18494022.0 \n", "ALT TECHNOLOGIES TRANSYLVANIA SRL 53072027.0 54277063.0 54588122.0 \n", "ALUTUS SA NaN NaN NaN \n", "ALZOCOM-TRANSPORT SRL 12785106.0 13720358.0 16841974.0 \n", "AMECO RENEWABLE ENERGY SRL 19744193.0 7623894.0 11285020.0 \n", "AMIGO & INTERCOST SRL 290602580.0 338871404.0 381852182.0 \n", "AMIGO SRL 19643902.0 22490359.0 28169310.0 \n", "APC UNIVERSAL PARTNER SRL NaN 0.0 17535928.0 \n", "APEMIN TUSNAD SA 41361947.0 45394719.0 51210314.0 \n", "AQUA CALIMANI SRL NaN NaN NaN \n", "AQUA NOVA HARGITA SRL NaN NaN NaN \n", "ARAMIS RO SRL NaN NaN NaN \n", "ARCON SRL 124968490.0 110394138.0 83022166.0 \n", "ARTEMOB INTERNATIONAL SRL 64999036.0 96337149.0 134053580.0 \n", "... ... ... ... \n", "TRICOMSERV SA 17599455.0 15453556.0 11980197.0 \n", "TRIMEX SERVICII SRL 10185155.0 13535129.0 8928863.0 \n", "TRIO IMPEX SRL NaN NaN NaN \n", "TROPICAL SRL 7113164.0 6656268.0 7698693.0 \n", "TURISM COVASNA SA 9665694.0 11254632.0 12120757.0 \n", "TUSNAD SA NaN NaN NaN \n", "UDVARHELYI HIRADO SRL NaN NaN NaN \n", "UNIC TRIO SRL NaN NaN NaN \n", "UNIO LUNCA SRL NaN NaN NaN \n", "UNIPREST INSTAL SRL 81287908.0 92938901.0 111860492.0 \n", "UPS DISTRIBUTION SRL 8323927.0 8901784.0 9939657.0 \n", "VALDEK IMPEX SRL 98072334.0 38466262.0 22250435.0 \n", "VALKES SRL 31885928.0 32843165.0 30626442.0 \n", "VBH ROMCOM SRL 46612739.0 49332868.0 54520221.0 \n", "VEL FUNGO SRL 8315513.0 14907258.0 26121250.0 \n", "VIADUCT SRL 30606802.0 26571799.0 23616230.0 \n", "VIASTEIN SRL 15236830.0 15295661.0 17168209.0 \n", "VIASTRADA SRL 7945073.0 9049705.0 12107718.0 \n", "VIKING SRL NaN NaN NaN \n", "VILLEX SRL NaN NaN NaN \n", "WABERER S ROMANIA SA 45080527.0 39478024.0 30033637.0 \n", "WALOR RO SRL 57782546.0 79335550.0 103680748.0 \n", "WEEKEND SRL 15555277.0 20504368.0 19455456.0 \n", "WERNETTO SRL 1813259.0 6602913.0 12704346.0 \n", "WIKEND FOREST IMPEX SRL 7843382.0 7195045.0 6952665.0 \n", "WONDERLAND SRL NaN NaN NaN \n", "ZABOLA ESTATE SRL NaN NaN NaN \n", "ZAMBELLI METAL SRL 27891895.0 34591562.0 42016920.0 \n", "ZARAH MODEN SRL 139752712.0 141121629.0 148531005.0 \n", "ZENCO TRANS SRL NaN NaN NaN \n", "\n", " 2014.2 2015.2 2016.2 2017.2 2014.3 \\\n", "A M C SRL 18.131 22.173 24.390 27.881 NaN \n", "ABC IMPEX SRL 30.364 31.956 33.072 36.540 0.253 \n", "ABRAZIV SRL 0.000 0.000 0.000 5.483 NaN \n", "ADIMAG COM IMPEX SRL 44.032 47.437 48.827 57.106 NaN \n", "AFEROM TRANS SRL 12.096 12.531 13.592 13.341 NaN \n", "AGER SRL 10.323 10.512 10.629 14.549 NaN \n", "AGM ECO CORPORATE SRL NaN NaN NaN NaN NaN \n", "AGRICO M SRL 5.702 6.377 7.643 9.400 NaN \n", "AGRO PAN STAR SRL 2.846 13.373 20.905 19.034 NaN \n", "AGRO ROM IMPEX SRL 21.672 29.093 43.731 52.824 NaN \n", "AGROPROD CARTOF SRL 0.695 6.258 9.739 6.144 NaN \n", "AGROWEST BMB SRL 11.026 9.992 10.108 10.272 NaN \n", "AIRQUEE SRL 12.507 17.489 19.581 20.263 0.102 \n", "ALEX & CO SA 13.851 15.773 15.610 16.943 0.080 \n", "ALIAT AUTO SRL 60.851 69.604 91.134 104.994 NaN \n", "ALLCOLORS SERV SRL NaN NaN NaN NaN NaN \n", "ALMI ROM SRL 11.363 12.418 14.488 18.494 NaN \n", "ALT TECHNOLOGIES TRANSYLVANIA SRL 37.935 53.072 54.277 54.588 0.243 \n", "ALUTUS SA NaN NaN NaN NaN NaN \n", "ALZOCOM-TRANSPORT SRL 10.427 12.785 13.720 16.842 NaN \n", "AMECO RENEWABLE ENERGY SRL 21.180 19.744 7.624 11.285 0.255 \n", "AMIGO & INTERCOST SRL 276.276 290.603 338.871 381.852 0.438 \n", "AMIGO SRL 17.291 19.644 22.490 28.169 NaN \n", "APC UNIVERSAL PARTNER SRL NaN NaN 0.000 17.536 NaN \n", "APEMIN TUSNAD SA 37.155 41.362 45.395 51.210 0.256 \n", "AQUA CALIMANI SRL NaN NaN NaN NaN NaN \n", "AQUA NOVA HARGITA SRL NaN NaN NaN NaN NaN \n", "ARAMIS RO SRL NaN NaN NaN NaN NaN \n", "ARCON SRL 120.247 124.968 110.394 83.022 0.747 \n", "ARTEMOB INTERNATIONAL SRL 62.059 64.999 96.337 134.054 0.121 \n", "... ... ... ... ... ... \n", "TRICOMSERV SA 16.389 17.599 15.454 11.980 0.188 \n", "TRIMEX SERVICII SRL 8.240 10.185 13.535 8.929 NaN \n", "TRIO IMPEX SRL NaN NaN NaN NaN NaN \n", "TROPICAL SRL 8.511 7.113 6.656 7.699 NaN \n", "TURISM COVASNA SA 10.079 9.666 11.255 12.121 0.120 \n", "TUSNAD SA NaN NaN NaN NaN NaN \n", "UDVARHELYI HIRADO SRL NaN NaN NaN NaN NaN \n", "UNIC TRIO SRL NaN NaN NaN NaN NaN \n", "UNIO LUNCA SRL NaN NaN NaN NaN NaN \n", "UNIPREST INSTAL SRL 65.084 81.288 92.939 111.860 NaN \n", "UPS DISTRIBUTION SRL 8.550 8.324 8.902 9.940 NaN \n", "VALDEK IMPEX SRL 64.206 98.072 38.466 22.250 0.361 \n", "VALKES SRL 36.662 31.886 32.843 30.626 0.026 \n", "VBH ROMCOM SRL 39.812 46.613 49.333 54.520 NaN \n", "VEL FUNGO SRL 7.089 8.316 14.907 26.121 NaN \n", "VIADUCT SRL 27.306 30.607 26.572 23.616 0.251 \n", "VIASTEIN SRL 12.025 15.237 15.296 17.168 NaN \n", "VIASTRADA SRL 8.452 7.945 9.050 12.108 0.445 \n", "VIKING SRL NaN NaN NaN NaN NaN \n", "VILLEX SRL NaN NaN NaN NaN NaN \n", "WABERER S ROMANIA SA 70.232 45.081 39.478 30.034 0.442 \n", "WALOR RO SRL 48.459 57.783 79.336 103.681 0.309 \n", "WEEKEND SRL 14.801 15.555 20.504 19.455 NaN \n", "WERNETTO SRL 1.813 1.813 6.603 12.704 0.040 \n", "WIKEND FOREST IMPEX SRL 5.228 7.843 7.195 6.953 NaN \n", "WONDERLAND SRL NaN NaN NaN NaN NaN \n", "ZABOLA ESTATE SRL NaN NaN NaN NaN NaN \n", "ZAMBELLI METAL SRL 28.480 27.892 34.592 42.017 0.209 \n", "ZARAH MODEN SRL 144.887 139.753 141.122 148.531 0.175 \n", "ZENCO TRANS SRL NaN NaN NaN NaN NaN \n", "\n", " 2015.3 2016.3 2017.3 Régió \\\n", "A M C SRL NaN NaN NaN Alsó-háromszék \n", "ABC IMPEX SRL 0.242 0.251 0.252 Udvarhelyszék \n", "ABRAZIV SRL NaN NaN NaN Gyergyószék \n", "ADIMAG COM IMPEX SRL NaN NaN NaN Marosszék \n", "AFEROM TRANS SRL NaN NaN NaN Csíkszék \n", "AGER SRL NaN NaN NaN Alsó-háromszék \n", "AGM ECO CORPORATE SRL NaN NaN NaN Udvarhelyszék \n", "AGRICO M SRL NaN NaN NaN Felső-háromszék \n", "AGRO PAN STAR SRL NaN NaN NaN Alsó-háromszék \n", "AGRO ROM IMPEX SRL NaN NaN NaN Marosszék \n", "AGROPROD CARTOF SRL NaN NaN NaN Felső-háromszék \n", "AGROWEST BMB SRL NaN NaN NaN Felső-háromszék \n", "AIRQUEE SRL 0.109 0.102 0.104 Alsó-háromszék \n", "ALEX & CO SA 0.091 0.108 0.118 Alsó-háromszék \n", "ALIAT AUTO SRL NaN NaN NaN Marosszék \n", "ALLCOLORS SERV SRL NaN NaN NaN Marosszék \n", "ALMI ROM SRL NaN NaN NaN Gyergyószék \n", "ALT TECHNOLOGIES TRANSYLVANIA SRL 0.302 0.292 0.276 Udvarhelyszék \n", "ALUTUS SA NaN NaN NaN Csíkszék \n", "ALZOCOM-TRANSPORT SRL NaN NaN NaN Csíkszék \n", "AMECO RENEWABLE ENERGY SRL 0.335 0.254 0.332 Gyergyószék \n", "AMIGO & INTERCOST SRL 0.469 0.468 0.486 Udvarhelyszék \n", "AMIGO SRL NaN NaN NaN Csíkszék \n", "APC UNIVERSAL PARTNER SRL NaN 0.000 0.126 Udvarhelyszék \n", "APEMIN TUSNAD SA 0.302 0.334 0.358 Csíkszék \n", "AQUA CALIMANI SRL NaN NaN NaN Gyergyószék \n", "AQUA NOVA HARGITA SRL NaN NaN NaN Udvarhelyszék \n", "ARAMIS RO SRL NaN NaN NaN Udvarhelyszék \n", "ARCON SRL 0.786 0.731 0.822 Alsó-háromszék \n", "ARTEMOB INTERNATIONAL SRL 0.128 0.189 0.232 Marosszék \n", "... ... ... ... ... \n", "TRICOMSERV SA 0.202 0.178 0.160 Alsó-háromszék \n", "TRIMEX SERVICII SRL NaN NaN NaN Felső-háromszék \n", "TRIO IMPEX SRL NaN NaN NaN Alsó-háromszék \n", "TROPICAL SRL NaN NaN NaN Gyergyószék \n", "TURISM COVASNA SA 0.116 0.114 0.115 Felső-háromszék \n", "TUSNAD SA NaN NaN NaN Csíkszék \n", "UDVARHELYI HIRADO SRL NaN NaN NaN Udvarhelyszék \n", "UNIC TRIO SRL NaN NaN NaN Csíkszék \n", "UNIO LUNCA SRL NaN NaN NaN Csíkszék \n", "UNIPREST INSTAL SRL NaN NaN NaN Marosszék \n", "UPS DISTRIBUTION SRL NaN NaN NaN Gyergyószék \n", "VALDEK IMPEX SRL 0.633 0.296 0.184 Alsó-háromszék \n", "VALKES SRL 0.032 0.037 0.039 Alsó-háromszék \n", "VBH ROMCOM SRL NaN NaN NaN Marosszék \n", "VEL FUNGO SRL NaN NaN NaN Csíkszék \n", "VIADUCT SRL 0.227 0.169 0.156 Udvarhelyszék \n", "VIASTEIN SRL NaN NaN NaN Alsó-háromszék \n", "VIASTRADA SRL 0.345 0.335 0.356 Gyergyószék \n", "VIKING SRL NaN NaN NaN Udvarhelyszék \n", "VILLEX SRL NaN NaN NaN Felső-háromszék \n", "WABERER S ROMANIA SA 0.618 0.564 0.429 Csíkszék \n", "WALOR RO SRL 0.354 0.451 0.482 Alsó-háromszék \n", "WEEKEND SRL NaN NaN NaN Alsó-háromszék \n", "WERNETTO SRL 0.040 0.106 0.249 Gyergyószék \n", "WIKEND FOREST IMPEX SRL NaN NaN NaN Gyergyószék \n", "WONDERLAND SRL NaN NaN NaN Felső-háromszék \n", "ZABOLA ESTATE SRL NaN NaN NaN Felső-háromszék \n", "ZAMBELLI METAL SRL 0.171 0.214 0.235 Alsó-háromszék \n", "ZARAH MODEN SRL 0.167 0.181 0.189 Felső-háromszék \n", "ZENCO TRANS SRL NaN NaN NaN Gyergyószék \n", "\n", " Hosszúság Szélesség Iparág \n", "A M C SRL 25.589216 45.839135 Kereskedelem \n", "ABC IMPEX SRL 25.290034 46.289768 Kisipar, műanyag \n", "ABRAZIV SRL 25.575165 46.717425 Kereskedelem \n", "ADIMAG COM IMPEX SRL 24.548819 46.537905 Építkezés \n", "AFEROM TRANS SRL 25.786071 46.361412 Szállítás \n", "AGER SRL 26.029142 45.667196 Kisipar, műanyag \n", "AGM ECO CORPORATE SRL 25.311729 46.316023 Élelmiszer \n", "AGRICO M SRL 26.132670 46.006632 Mezőgazdaság \n", "AGRO PAN STAR SRL 25.793258 45.870001 Élelmiszer \n", "AGRO ROM IMPEX SRL 24.531839 46.526013 Kereskedelem \n", "AGROPROD CARTOF SRL 26.137711 45.993911 Mezőgazdaság \n", "AGROWEST BMB SRL 26.034927 45.959291 Mezőgazdaság \n", "AIRQUEE SRL 25.813948 45.863252 Kereskedelem \n", "ALEX & CO SA 25.804319 45.773468 Fa, bútor \n", "ALIAT AUTO SRL 24.540352 46.526409 Kereskedelem \n", "ALLCOLORS SERV SRL 24.416343 46.471794 Szolgáltatás \n", "ALMI ROM SRL 25.575578 46.714488 Élelmiszer \n", "ALT TECHNOLOGIES TRANSYLVANIA SRL 25.216672 46.385158 Kisipar, műanyag \n", "ALUTUS SA 25.772309 46.369458 Kisipar, műanyag \n", "ALZOCOM-TRANSPORT SRL 25.807297 46.356965 Szállítás \n", "AMECO RENEWABLE ENERGY SRL 25.574541 46.718254 Fa, bútor \n", "AMIGO & INTERCOST SRL 25.304518 46.314643 Kereskedelem \n", "AMIGO SRL 25.790373 46.359746 Kereskedelem \n", "APC UNIVERSAL PARTNER SRL 25.313356 46.316934 Kereskedelem \n", "APEMIN TUSNAD SA 25.911948 46.206866 Ásványvíz \n", "AQUA CALIMANI SRL 25.350802 46.922981 Ásványvíz \n", "AQUA NOVA HARGITA SRL 25.309561 46.314822 Szolgáltatás \n", "ARAMIS RO SRL 25.306127 46.311619 Szolgáltatás \n", "ARCON SRL 25.789279 45.868490 Kisipar, műanyag \n", "ARTEMOB INTERNATIONAL SRL 25.075010 46.575623 Fa, bútor \n", "... ... ... ... \n", "TRICOMSERV SA 25.786644 45.855076 Kisipar, műanyag \n", "TRIMEX SERVICII SRL 26.063746 46.040239 Építkezés \n", "TRIO IMPEX SRL 25.850000 45.950000 Szállítás \n", "TROPICAL SRL 25.500000 46.700000 Szállítás \n", "TURISM COVASNA SA 26.166816 45.844993 Vendéglátó \n", "TUSNAD SA 25.860563 46.146941 Vendéglátó \n", "UDVARHELYI HIRADO SRL 25.302565 46.300650 Szolgáltatás \n", "UNIC TRIO SRL 25.806393 46.655610 Élelmiszer \n", "UNIO LUNCA SRL 25.954123 46.559288 Élelmiszer \n", "UNIPREST INSTAL SRL 24.531839 46.526013 Szolgáltatás \n", "UPS DISTRIBUTION SRL 25.602353 46.715585 Szolgáltatás \n", "VALDEK IMPEX SRL 25.789340 45.865936 Építkezés \n", "VALKES SRL 25.806651 45.855129 Kisipar, műanyag \n", "VBH ROMCOM SRL 24.540352 46.526409 Kisipar, műanyag \n", "VEL FUNGO SRL 25.753152 46.437482 Mezőgazdaság \n", "VIADUCT SRL 25.320777 46.322821 Építkezés \n", "VIASTEIN SRL 25.799716 45.770781 Építkezés \n", "VIASTRADA SRL 25.598123 46.696028 Szállítás \n", "VIKING SRL 25.293976 46.307330 Építkezés \n", "VILLEX SRL 26.135058 45.999479 Kereskedelem \n", "WABERER S ROMANIA SA 25.748457 46.370803 Szállítás \n", "WALOR RO SRL 25.818515 45.861235 Kisipar, műanyag \n", "WEEKEND SRL 25.795791 45.865823 Kereskedelem \n", "WERNETTO SRL 25.585527 46.721211 Építkezés \n", "WIKEND FOREST IMPEX SRL 25.442658 46.796304 Építkezés \n", "WONDERLAND SRL 26.063746 46.040239 Építkezés \n", "ZABOLA ESTATE SRL 26.198029 45.891556 Vendéglátó \n", "ZAMBELLI METAL SRL 25.818515 45.861235 Szolgáltatás \n", "ZARAH MODEN SRL 26.135967 45.996939 Textil \n", "ZENCO TRANS SRL 25.353404 46.926030 Szállítás \n", "\n", "[424 rows x 20 columns]" ] }, "execution_count": 11, "metadata": {}, "output_type": "execute_result" } ], "source": [ "data3" ] }, { "cell_type": "code", "execution_count": 12, "metadata": { "ExecuteTime": { "end_time": "2018-12-16T19:48:28.671193Z", "start_time": "2018-12-16T19:48:28.414197Z" } }, "outputs": [], "source": [ "from mpl_toolkits.mplot3d import axes3d" ] }, { "cell_type": "code", "execution_count": 63, "metadata": { "ExecuteTime": { "end_time": "2018-12-16T20:12:19.057166Z", "start_time": "2018-12-16T20:12:19.048163Z" } }, "outputs": [], "source": [ "x=list(data3['Hosszúság'].values)\n", "y=list(data3['Szélesség'].values)\n", "s=data3['2017.2'].values\n", "formfactor=0.68\n", "s=list((s*1000)**formfactor)" ] }, { "cell_type": "code", "execution_count": 64, "metadata": { "ExecuteTime": { "end_time": "2018-12-16T20:12:19.735169Z", "start_time": "2018-12-16T20:12:19.725174Z" } }, "outputs": [], "source": [ "cs={\"Élelmiszer\":\"#543005\",\n", "\"Ásványvíz\":\"#9e0142\",\n", "\"Mezőgazdaság\":\"#d53e4f\",\n", "\"Kereskedelem\":\"#f46d43\",\n", "\"Szolgáltatás\":\"#fdae61\",\n", "\"Vendéglátó\":\"#fee08b\",\n", "\"Szállítás\":\"#ffffbf\",\n", "\"Textil\":\"#e6f598\",\n", "\"Gyógyszer, vegyipar\":\"#abdda4\",\n", "\"Építkezés\":\"#66c2a5\",\n", "\"Fa, bútor\":\"#3288bd\",\n", "\"Kisipar, műanyag\":\"#5e4fa2\",\n", "\"Nehézipar, bányászat\":\"#40004b\",\n", "\"Energia\":\"#762a83\"}" ] }, { "cell_type": "code", "execution_count": 65, "metadata": { "ExecuteTime": { "end_time": "2018-12-16T20:12:20.268163Z", "start_time": "2018-12-16T20:12:20.256167Z" } }, "outputs": [], "source": [ "sectors2=list(cs.keys())\n", "c=[cs[data3['Iparág'].values[k]] for k in range(len(data3['Iparág'].values))]" ] }, { "cell_type": "code", "execution_count": 87, "metadata": { "ExecuteTime": { "end_time": "2018-12-16T20:20:18.263862Z", "start_time": "2018-12-16T20:19:18.083579Z" } }, "outputs": [ { "name": "stderr", "output_type": "stream", "text": [ "C:\\ProgramData\\Anaconda3\\lib\\site-packages\\numpy\\core\\fromnumeric.py:83: RuntimeWarning: invalid value encountered in reduce\n", " return ufunc.reduce(obj, axis, dtype, out, **passkwargs)\n" ] }, { "ename": "TypeError", "evalue": "Object of type ndarray is not JSON serializable", "output_type": "error", "traceback": [ "\u001b[1;31m---------------------------------------------------------------------------\u001b[0m", "\u001b[1;31mTypeError\u001b[0m Traceback (most recent call last)", "\u001b[1;32mC:\\ProgramData\\Anaconda3\\lib\\site-packages\\IPython\\core\\formatters.py\u001b[0m in \u001b[0;36m__call__\u001b[1;34m(self, obj)\u001b[0m\n\u001b[0;32m 339\u001b[0m \u001b[1;32mpass\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 340\u001b[0m \u001b[1;32melse\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m--> 341\u001b[1;33m \u001b[1;32mreturn\u001b[0m \u001b[0mprinter\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mobj\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m 342\u001b[0m \u001b[1;31m# Finally look for special method names\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 343\u001b[0m \u001b[0mmethod\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mget_real_method\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mobj\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mprint_method\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n", "\u001b[1;32mC:\\ProgramData\\Anaconda3\\lib\\site-packages\\mpld3\\_display.py\u001b[0m in \u001b[0;36m\u001b[1;34m(fig, kwds)\u001b[0m\n\u001b[0;32m 408\u001b[0m \u001b[0mformatter\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mip\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mdisplay_formatter\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mformatters\u001b[0m\u001b[1;33m[\u001b[0m\u001b[1;34m'text/html'\u001b[0m\u001b[1;33m]\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 409\u001b[0m formatter.for_type(Figure,\n\u001b[1;32m--> 410\u001b[1;33m lambda fig, kwds=kwargs: fig_to_html(fig, **kwds))\n\u001b[0m\u001b[0;32m 411\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 412\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n", "\u001b[1;32mC:\\ProgramData\\Anaconda3\\lib\\site-packages\\mpld3\\_display.py\u001b[0m in \u001b[0;36mfig_to_html\u001b[1;34m(fig, d3_url, mpld3_url, no_extras, template_type, figid, use_http, **kwargs)\u001b[0m\n\u001b[0;32m 249\u001b[0m \u001b[0md3_url\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0md3_url\u001b[0m\u001b[1;33m,\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 250\u001b[0m \u001b[0mmpld3_url\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mmpld3_url\u001b[0m\u001b[1;33m,\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m--> 251\u001b[1;33m \u001b[0mfigure_json\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mjson\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mdumps\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mfigure_json\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mcls\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mNumpyEncoder\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m,\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m 252\u001b[0m \u001b[0mextra_css\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mextra_css\u001b[0m\u001b[1;33m,\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 253\u001b[0m extra_js=extra_js)\n", "\u001b[1;32mC:\\ProgramData\\Anaconda3\\lib\\json\\__init__.py\u001b[0m in \u001b[0;36mdumps\u001b[1;34m(obj, skipkeys, ensure_ascii, check_circular, allow_nan, cls, indent, separators, default, sort_keys, **kw)\u001b[0m\n\u001b[0;32m 236\u001b[0m \u001b[0mcheck_circular\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mcheck_circular\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mallow_nan\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mallow_nan\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mindent\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mindent\u001b[0m\u001b[1;33m,\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 237\u001b[0m \u001b[0mseparators\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mseparators\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mdefault\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mdefault\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0msort_keys\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0msort_keys\u001b[0m\u001b[1;33m,\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m--> 238\u001b[1;33m **kw).encode(obj)\n\u001b[0m\u001b[0;32m 239\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 240\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n", "\u001b[1;32mC:\\ProgramData\\Anaconda3\\lib\\json\\encoder.py\u001b[0m in \u001b[0;36mencode\u001b[1;34m(self, o)\u001b[0m\n\u001b[0;32m 197\u001b[0m \u001b[1;31m# exceptions aren't as detailed. The list call should be roughly\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 198\u001b[0m \u001b[1;31m# equivalent to the PySequence_Fast that ''.join() would do.\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m--> 199\u001b[1;33m \u001b[0mchunks\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0miterencode\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mo\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0m_one_shot\u001b[0m\u001b[1;33m=\u001b[0m\u001b[1;32mTrue\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m 200\u001b[0m \u001b[1;32mif\u001b[0m \u001b[1;32mnot\u001b[0m \u001b[0misinstance\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mchunks\u001b[0m\u001b[1;33m,\u001b[0m \u001b[1;33m(\u001b[0m\u001b[0mlist\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mtuple\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 201\u001b[0m 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\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 259\u001b[0m def _make_iterencode(markers, _default, _encoder, _indent, _floatstr,\n", "\u001b[1;32mC:\\ProgramData\\Anaconda3\\lib\\site-packages\\mpld3\\_display.py\u001b[0m in \u001b[0;36mdefault\u001b[1;34m(self, obj)\u001b[0m\n\u001b[0;32m 136\u001b[0m numpy.float64)):\n\u001b[0;32m 137\u001b[0m \u001b[1;32mreturn\u001b[0m \u001b[0mfloat\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mobj\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m--> 138\u001b[1;33m \u001b[1;32mreturn\u001b[0m \u001b[0mjson\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mJSONEncoder\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mdefault\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mself\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mobj\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m 139\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 140\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n", "\u001b[1;32mC:\\ProgramData\\Anaconda3\\lib\\json\\encoder.py\u001b[0m in \u001b[0;36mdefault\u001b[1;34m(self, o)\u001b[0m\n\u001b[0;32m 177\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 178\u001b[0m \"\"\"\n\u001b[1;32m--> 179\u001b[1;33m raise TypeError(f'Object of type {o.__class__.__name__} '\n\u001b[0m\u001b[0;32m 180\u001b[0m f'is not JSON serializable')\n\u001b[0;32m 181\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n", "\u001b[1;31mTypeError\u001b[0m: Object of type ndarray is not JSON serializable" ] }, { "data": { "image/png": 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" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "fig=plt.figure(figsize=(14,14))\n", "ax=axes3d.Axes3D(fig,azim=-70,elev=55)\n", "ax._axis3don = False\n", "\n", "scale=1\n", "xlim=np.array([24.25,26.5])\n", "ylim=np.array([45.57,48.00])\n", "\n", "points=[]\n", "for j in range(len(x)):\n", " index=j\n", " hindex=0\n", " r=(s[index]/100000000)**0.25\n", " for p in range(len(points)):\n", " if (np.sqrt((points[p][0]-x[index])**2+(points[p][1]-y[index])**2)<((abs(r-points[p][2]))*1.3)):\n", " hindex+=1 \n", " \n", " points.append([x[index],y[index],r])\n", " \n", " # Cylindrical shell \n", " phi = np.linspace(0, 2 * np.pi, 100) \n", " r1 = np.ones(100) \n", " h1 = np.linspace(hindex, hindex+1, 100) \n", "\n", " x1 = r * np.outer(np.cos(phi), r1) + x[index]\n", " y1 = r * np.outer(np.sin(phi), r1) + y[index]\n", " z1 = 1 * np.outer(np.ones(np.size(r1)), h1) \n", "\n", " # Top cover \n", " phi_a = np.linspace(0, 2 * np.pi, 100) \n", " h2 = np.ones(100) \n", " r2 = np.linspace(0, 1, 100) \n", "\n", " phi_grid, r_grid = np.meshgrid(phi_a, r2)\n", " x2 = r * np.cos(phi_grid) * r_grid + x[index]\n", " y2 = r * np.sin(phi_grid) * r_grid + y[index]\n", " z2 = (hindex+1) * np.ones([100,100])\n", "\n", " #walls\n", " ax.plot_surface(x1*scale, y1*scale, z1, rstride=5, cstride=100, linewidth=0.1, alpha=1, shade=False,color=c[index]) \n", " #top cyl\n", " ax.plot_surface(x2*scale, y2*scale, z2, rstride=100, cstride=34, linewidth=0.1, alpha=1, shade=False,color=c[index]) \n", "\n", "for w in range(len(sectors2)):\n", " r=0.033\n", " # Cylindrical shell \n", " phi = np.linspace(0, 2 * np.pi, 100) \n", " r1 = np.ones(100) \n", " h1 = np.linspace(w, w+1, 100) \n", "\n", " x1 = r * np.outer(np.cos(phi), r1) + 26.05-0.02*w\n", " y1 = r * np.outer(np.sin(phi), r1) + 47.34+0.03*w\n", " z1 = 1 * np.outer(np.ones(np.size(r1)), h1) \n", "\n", " # Top cover \n", " phi_a = np.linspace(0, 2 * np.pi, 100) \n", " h2 = np.ones(100) \n", " r2 = np.linspace(0, 1, 100) \n", "\n", " phi_grid, r_grid = np.meshgrid(phi_a, r2)\n", " x2 = r * np.cos(phi_grid) * r_grid + 26.05-0.02*w\n", " y2 = r * np.sin(phi_grid) * r_grid + 47.34+0.03*w\n", " z2 = (w+1) * np.ones([100,100])\n", "\n", " ax.plot_surface(x1*scale, y1*scale, z1, rstride=5, cstride=100, linewidth=0.1, alpha=1, shade=False,color=colors[w]) \n", " ax.plot_surface(x2*scale, y2*scale, z2, rstride=100, cstride=34, linewidth=0.1, alpha=1, shade=False,color=colors[w])\n", " ax.text2D(0.71-w*0.0023, 0.41+w*0.011,sectors2[w], transform=ax.transAxes)\n", "\n", "ax.set_zlim([0,70])\n", "ax.set_xlim(xlim)\n", "ax.set_ylim(ylim)\n", "\n", "plt.show()" ] }, { "cell_type": "code", "execution_count": 88, "metadata": { "ExecuteTime": { "end_time": "2018-12-16T20:20:30.653847Z", "start_time": "2018-12-16T20:20:18.268857Z" } }, "outputs": [ { "name": "stderr", "output_type": "stream", "text": [ "C:\\ProgramData\\Anaconda3\\lib\\site-packages\\numpy\\core\\fromnumeric.py:83: RuntimeWarning: invalid value encountered in reduce\n", " return ufunc.reduce(obj, axis, dtype, out, **passkwargs)\n" ] } ], "source": [ "fig.savefig('3d.svg')" ] } ], "metadata": { "kernelspec": { "display_name": "Python 3", "language": "python", "name": "python3" }, "language_info": { "codemirror_mode": { "name": "ipython", "version": 3 }, "file_extension": ".py", "mimetype": "text/x-python", "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", "version": "3.7.4" }, "toc": { "base_numbering": 1, "nav_menu": {}, "number_sections": true, "sideBar": true, "skip_h1_title": false, "title_cell": "Table of Contents", "title_sidebar": "Contents", "toc_cell": false, "toc_position": {}, "toc_section_display": true, "toc_window_display": false } }, "nbformat": 4, "nbformat_minor": 4 }