agticultural_production
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1 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', ' ': '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
2 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]: Share of products in agricultutal production (1)(2010) EU-27 \ 10 Wheat (2) Rye (2) Oats (2) Barley (2) Maize (2) Rice (2) Sugarbeet Tobacco Olive oil Oilseeds (2) Fruit (3) Fresh vegetables (3) Wine and must Seeds (4) Textile fibres Hops Milk Cattle Pigs Sheep and goats Eggs Poultry 5.0 Belgium Bulgaria Czech Republic Denmark Germany Estonia Ireland
3 Greece Spain France Italia Cyprus Latvia Lithuania Luxembourg \ Hungary
4 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', ' ': '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
5 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', ' ': '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
6 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
7 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
8 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
9 In [ ]: 9
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