agticultural_production March 20, 2017 In [5]: import pandas as np data = np.read_csv("2011_agricultural products.csv") data = data.rename(columns={'unnamed: 1': 'EU-27', 'Unnamed: 2': 'Belgium',, 'Unnamed: 6': 'Germany', 'Unnamed: 7': 'Estoni, 'Unnamed: 11': 'France', 'Unnamed: 12': 'Itali, '(%)': 'Luxembourg', '19.02.2012': 'Hungary'}) data_2010 = data.drop(data.index[[0,1,2,3,4,5,6,7,8,9,32,33,35,36]]).head(2 data_2010['eu-27'] = data_2010['eu-27'].str.replace(",",".") data_2010['belgium'] = data_2010['belgium'].str.replace(",",".") data_2010['bulgaria'] = data_2010['bulgaria'].str.replace(",",".") data_2010['bulgaria'] = data_2010['bulgaria'].str.replace(":","0.0") data_2010['czech Republic'] = data_2010['czech Republic'].str.replace(","," data_2010['denmark'] = data_2010['denmark'].str.replace(",",".") data_2010['germany'] = data_2010['germany'].str.replace(",",".") data_2010['estonia'] = data_2010['estonia'].str.replace(",",".") data_2010['ireland'] = data_2010['ireland'].str.replace(",",".") data_2010['ireland'] = data_2010['ireland'].str.replace(":","0.0") data_2010['greece'] = data_2010['greece'].str.replace(",",".") data_2010['spain'] = data_2010['spain'].str.replace(",",".") data_2010['france'] = data_2010['france'].str.replace(",",".") data_2010['italia'] = data_2010['italia'].str.replace(",",".") data_2010['cyprus'] = data_2010['cyprus'].str.replace(",",".") data_2010['latvia'] = data_2010['latvia'].str.replace(",",".") data_2010['latvia'] = data_2010['latvia'].str.replace(":","0.0") data_2010['lithuania'] = data_2010['lithuania'].str.replace(",",".") data_2010['luxembourg'] = data_2010['luxembourg'].str.replace(",",".") data_2010['hungary'] = data_2010['hungary'].str.replace(",",".") data_2010['belgium'] = data_2010['belgium'].astype(float) data_2010['bulgaria'] = data_2010['bulgaria'].astype(float) data_2010['czech Republic'] = data_2010['czech Republic'].astype(float) data_2010['denmark'] = data_2010['denmark'].astype(float) data_2010['germany'] = data_2010['germany'].astype(float) data_2010['estonia'] = data_2010['estonia'].astype(float) data_2010['ireland'] = data_2010['ireland'].astype(float) data_2010['greece'] = data_2010['greece'].astype(float) 1
data_2010['spain'] = data_2010['spain'].astype(float) data_2010['france'] = data_2010['france'].astype(float) data_2010['italia'] = data_2010['italia'].astype(float) data_2010['cyprus'] = data_2010['cyprus'].astype(float) data_2010['latvia'] = data_2010['latvia'].astype(float) data_2010['lithuania'] = data_2010['lithuania'].astype(float) data_2010['luxembourg'] = data_2010['luxembourg'].astype(float) data_2010['hungary'] = data_2010['hungary'].astype(float) product_arr = [ "Wheat", "Rye", "Oats", "Barley", "Maize", "Sugarbeet", "Tobacco", "Olive oil", "Oilseeds", "Fruit" "Wine and must", "Seeds", "Textile fibres", "Hops", "Milk "Pigs", "Sheep and goats", "Eggs", "Poultry"] data_2010 Out[5]: 3.1.1 Share of products in agricultutal production (1)(2010) EU-27 \ 10 Wheat (2) 6.2 11 Rye (2) 0.3 12 Oats (2) 0.4 13 Barley (2) 2.0 14 Maize (2) 2.8 15 Rice (2) 0.3 16 Sugarbeet 0.9 17 Tobacco 0.2 18 Olive oil 1.2 19 Oilseeds (2) 2.7 20 Fruit (3) 6.5 21 Fresh vegetables (3) 8.7 22 Wine and must 4.3 23 Seeds (4) 0.3 24 Textile fibres 0.2 25 Hops 0.1 26 Milk 13.8 27 Cattle 8.2 28 Pigs 8.9 29 Sheep and goats 1.4 30 Eggs 2.1 31 Poultry 5.0 Belgium Bulgaria Czech Republic Denmark Germany Estonia Ireland 10 5.0 12.5 15.2 8.8 8.2 9.3 1.5 11 0.0 0.0 0.4 0.5 0.8 0.6 0.0 12 0.1 0.2 0.4 0.4 0.2 1.0 0.3 13 0.8 2.1 5.1 5.2 2.6 6.2 3.1 14 0.4 6.7 2.7 0.0 1.5 0.0 0.0 2
15 0.0 0.2 0.0 0.0 0.0 0.0 0.0 16 1.5 0.0 2.1 1.1 1.2 0.0 0.0 17 0.0 2.3 0.0 0.0 0.1 0.0 0.0 18 0.0 0.0 0.0 0.0 0.0 0.0 0.0 19 0.4 13.8 9.9 2.2 3.9 8.2 0.0 20 4.5 4.0 1.0 0.3 0.9 0.9 0.6 21 12.1 5.4 1.5 1.9 4.0 6.0 3.4 22 0.0 0.0 0.6 0.0 2.2 0.0 0.0 23 0.4 0.0 0.4 0.7 0.1 0.1 0.0 24 0.2 0.0 0.0 0.0 0.0 0.0 0.0 25 0.0 0.0 1.0 0.0 0.3 0.0 0.0 26 12.4 11.4 18.3 17.4 19.7 28.5 27.3 27 15.3 3.8 6.2 3.9 6.9 5.4 27.2 28 18.2 4.2 9.0 27.4 12.6 11.2 6.0 29 0.2 4.2 0.0 0.1 0.3 0.5 2.9 30 1.3 3.5 2.0 0.9 1.9 2.0 0.7 31 5.5 5.5 5.0 2.3 4.1 3.3 2.3 Greece Spain France Italia Cyprus Latvia Lithuania Luxembourg \ 10 2.8 2.9 9.6 3.3 0.6 16.9 15.5 5.3 11 0.0 0.1 0.0 0.0 0.0 0.9 0.7 0.3 12 0.2 0.4 0.1 0.1 0.0 1.2 0.7 0.3 13 0.5 3.4 2.0 0.4 0.9 3.1 4.5 2.4 14 4.3 1.8 4.1 3.4 0.0 0.0 0.5 0.1 15 0.6 0.8 0.1 1.0 0.0 0.0 0.0 0.0 16 0.4 0.3 1.2 0.3 0.0 0.0 1.2 0.0 17 0.7 0.2 0.1 0.7 0.0 0.0 0.0 0.0 18 6.8 4.8 0.0 3.5 3.0 0.0 0.0 0.0 19 0.3 0.9 3.9 0.5 0.1 8.1 8.1 1.9 20 15.7 16.9 4.8 11.8 18.7 0.4 0.4 0.7 21 18.2 15.4 5.0 13.0 11.9 4.5 3.0 1.0 22 0.4 2.1 12.3 8.6 0.0 0.0 0.0 7.7 23 0.1 0.0 0.2 0.6 0.4 0.5 0.1 0.1 24 5.6 0.3 0.2 0.0 0.0 0.0 0.0 0.0 25 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 26 12.3 6.4 12.1 10.4 17.3 21.4 20.4 30.3 27 2.7 5.6 11.3 7.5 1.5 4.4 5.4 19.6 28 2.3 12.4 4.4 5.7 9.6 7.9 7.3 7.2 29 7.1 2.2 1.2 0.5 3.7 0.3 0.2 0.3 30 1.0 2.4 1.2 2.5 2.8 4.6 2.5 1.1 31 1.7 4.9 4.8 4.7 11.9 3.4 4.2 0.2 Hungary 10 8.9 11 0.1 12 0.2 13 1.8 14 15.9 3
15 0.0 16 0.4 17 0.1 18 0.0 19 8.7 20 5.2 21 7.6 22 1.1 23 0.1 24 0.0 25 0.0 26 7.2 27 2.2 28 10.1 29 0.8 30 3.0 31 10.9 In [6]: import pandas as np data = np.read_csv("2012_agricultural products.csv") data = data.rename(columns={'unnamed: 1': 'EU-27', 'Unnamed: 2': 'Belgium',, 'Unnamed: 6': 'Germany', 'Unnamed: 7': 'Estoni, 'Unnamed: 11': 'France', 'Unnamed: 12': 'Itali, '(%)': 'Luxembourg', '14.12.2012': 'Hungary'}) data_2011 = data.drop(data.index[[0,1,2,3,4,5,6,7,8,32,33,35,36]]).head(22) data_2011['eu-27'] = data_2011['eu-27'].str.replace(",",".") data_2011['belgium'] = data_2011['belgium'].str.replace(",",".") data_2011['bulgaria'] = data_2011['bulgaria'].str.replace(",",".") data_2011['bulgaria'] = data_2011['bulgaria'].str.replace(":","0.0") data_2011['czech Republic'] = data_2011['czech Republic'].str.replace(","," data_2011['denmark'] = data_2011['denmark'].str.replace(",",".") data_2011['germany'] = data_2011['germany'].str.replace(",",".") data_2011['estonia'] = data_2011['estonia'].str.replace(",",".") data_2011['ireland'] = data_2011['ireland'].str.replace(",",".") data_2011['ireland'] = data_2011['ireland'].str.replace(":","0.0") data_2011['greece'] = data_2011['greece'].str.replace(",",".") data_2011['spain'] = data_2011['spain'].str.replace(",",".") data_2011['france'] = data_2011['france'].str.replace(",",".") data_2011['italia'] = data_2011['italia'].str.replace(",",".") data_2011['cyprus'] = data_2011['cyprus'].str.replace(",",".") data_2011['latvia'] = data_2011['latvia'].str.replace(",",".") data_2011['latvia'] = data_2011['latvia'].str.replace(":","0.0") data_2011['lithuania'] = data_2011['lithuania'].str.replace(",",".") data_2011['luxembourg'] = data_2011['luxembourg'].str.replace(",",".") data_2011['hungary'] = data_2011['hungary'].str.replace(",",".") data_2011['belgium'] = data_2011['belgium'].astype(float) 4
data_2011['bulgaria'] = data_2011['bulgaria'].astype(float) data_2011['czech Republic'] = data_2011['czech Republic'].astype(float) data_2011['denmark'] = data_2011['denmark'].astype(float) data_2011['germany'] = data_2011['germany'].astype(float) data_2011['estonia'] = data_2011['estonia'].astype(float) data_2011['ireland'] = data_2011['ireland'].astype(float) data_2011['greece'] = data_2011['greece'].astype(float) data_2011['spain'] = data_2011['spain'].astype(float) data_2011['france'] = data_2011['france'].astype(float) data_2011['italia'] = data_2011['italia'].astype(float) data_2011['cyprus'] = data_2011['cyprus'].astype(float) data_2011['latvia'] = data_2011['latvia'].astype(float) data_2011['lithuania'] = data_2011['lithuania'].astype(float) data_2011['luxembourg'] = data_2011['luxembourg'].astype(float) data_2011['hungary'] = data_2011['hungary'].astype(float) In [7]: import pandas as np data = np.read_csv("2013_agricultural products.csv") data = data.rename(columns={'unnamed: 1': 'EU-27', 'Unnamed: 2': 'Belgium',, 'Unnamed: 6': 'Germany', 'Unnamed: 7': 'Estoni, 'Unnamed: 11': 'France', 'Unnamed: 12': 'Itali, '(%)': 'Luxembourg', '11.12.2013': 'Hungary'}) data_2012 = data.drop(data.index[[0,1,2,3,4,5,6,7,8,32,33,35,36]]).head(22) data_2012['eu-27'] = data_2012['eu-27'].str.replace(",",".") data_2012['belgium'] = data_2012['belgium'].str.replace(",",".") data_2012['bulgaria'] = data_2012['bulgaria'].str.replace(",",".") data_2012['bulgaria'] = data_2012['bulgaria'].str.replace(":","0.0") data_2012['czech Republic'] = data_2012['czech Republic'].str.replace(","," data_2012['denmark'] = data_2012['denmark'].str.replace(",",".") data_2012['germany'] = data_2012['germany'].str.replace(",",".") data_2012['estonia'] = data_2012['estonia'].str.replace(",",".") data_2012['ireland'] = data_2012['ireland'].str.replace(",",".") data_2012['ireland'] = data_2012['ireland'].str.replace(":","0.0") data_2012['greece'] = data_2012['greece'].str.replace(",",".") data_2012['spain'] = data_2012['spain'].str.replace(",",".") data_2012['france'] = data_2012['france'].str.replace(",",".") data_2012['italia'] = data_2012['italia'].str.replace(",",".") data_2012['cyprus'] = data_2012['cyprus'].str.replace(",",".") data_2012['latvia'] = data_2012['latvia'].str.replace(",",".") data_2012['lithuania'] = data_2012['lithuania'].str.replace(",",".") data_2012['luxembourg'] = data_2012['luxembourg'].str.replace(",",".") data_2012['hungary'] = data_2012['hungary'].str.replace(",",".") data_2012['belgium'] = data_2012['belgium'].astype(float) data_2012['bulgaria'] = data_2012['bulgaria'].astype(float) data_2012['czech Republic'] = data_2012['czech Republic'].astype(float) data_2012['denmark'] = data_2012['denmark'].astype(float) 5
data_2012['germany'] = data_2012['germany'].astype(float) data_2012['estonia'] = data_2012['estonia'].astype(float) data_2012['ireland'] = data_2012['ireland'].astype(float) data_2012['greece'] = data_2012['greece'].astype(float) data_2012['spain'] = data_2012['spain'].astype(float) data_2012['france'] = data_2012['france'].astype(float) data_2012['italia'] = data_2012['italia'].astype(float) data_2012['cyprus'] = data_2012['cyprus'].astype(float) data_2012['latvia'] = data_2012['latvia'].astype(float) data_2012['lithuania'] = data_2012['lithuania'].astype(float) data_2012['luxembourg'] = data_2012['luxembourg'].astype(float) data_2012['hungary'] = data_2012['hungary'].astype(float) In [8]: data_2010_mean = data_2010.mean(axis=1) data_2010_mean = data_2010_mean.values data_2011_mean = data_2011.mean(axis=1) data_2011_mean = data_2011_mean.values data_2012_mean = data_2012.mean(axis=1) data_2012_mean = data_2012_mean.values In [9]: import numpy from matplotlib import pyplot as plt hist, bins = numpy.histogram(data_2010_mean, bins = 18, range = (0, 18)) width = 0.7 * (bins[1] - bins[0]) center = (bins[:-1] + bins[1:]) / 2 plt.bar(center, hist, align='center', width=width) plt.xlim(0, 18) plt.xticks(bins) plt.title("") plt.xlabel("") Out[9]: <matplotlib.text.text at 0x20af17eedd8> 6
In [10]: %matplotlib inline arraynum = [1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17,18,19,20,21,22] plt.scatter(arraynum, data_2010_mean, label = "2010") plt.scatter(arraynum, data_2011_mean, label = "2011") plt.scatter(arraynum, data_2011_mean, label = "2012") hist, bins = numpy.histogram(data_2010_mean, bins = 23, range = (0, 23)) width = 0.7 * (bins[1] - bins[0]) plt.xlim(0, 22) plt.xticks(bins) plt.xlabel('products') plt.ylabel('percentage') Out[10]: <matplotlib.text.text at 0x20af2a24d30> 7
In [12]: fig = plt.figure() ax1 = fig.add_subplot(111) ax1.scatter(arraynum, data_2010_mean, label = "2010") ax1.scatter(arraynum, data_2011_mean, label = "2011") ax1.scatter(arraynum, data_2012_mean, label = "2012") plt.title("mean of Agricultural Harvest in European Countries") ax1.set_xlabel('products') ax1.set_ylabel('percentage') plt.legend(loc='upper right'); plt.show() 8
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