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Patents Ratio North and Ibero Americas
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plots.ipynb
{
"cells": [
{
"cell_type": "code",
"execution_count": 20,
"id": "e071d481",
"metadata": {},
"outputs": [],
"source": [
"import pandas as pd\n",
"import numpy as np\n",
"import matplotlib.pyplot as plt"
]
},
{
"cell_type": "code",
"execution_count": 21,
"id": "c39fc403",
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
"<div>\n",
"<style scoped>\n",
" .dataframe tbody tr th:only-of-type {\n",
" vertical-align: middle;\n",
" }\n",
"\n",
" .dataframe tbody tr th {\n",
" vertical-align: top;\n",
" }\n",
"\n",
" .dataframe thead th {\n",
" text-align: right;\n",
" }\n",
"</style>\n",
"<table border=\"1\" class=\"dataframe\">\n",
" <thead>\n",
" <tr style=\"text-align: right;\">\n",
" <th></th>\n",
" <th>Office</th>\n",
" <th>Statistics</th>\n",
" <th>2020</th>\n",
" <th>2021</th>\n",
" <th>2022</th>\n",
" <th>2023</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>0</th>\n",
" <td>Argentina</td>\n",
" <td>1.1 - Patent applications</td>\n",
" <td>3492.0</td>\n",
" <td>3669.0</td>\n",
" <td>3576.0</td>\n",
" <td>3418.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1</th>\n",
" <td>Argentina</td>\n",
" <td>1.2 - Share of non-resident patent applications</td>\n",
" <td>73.4</td>\n",
" <td>88.9</td>\n",
" <td>87.6</td>\n",
" <td>87.7</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2</th>\n",
" <td>Argentina</td>\n",
" <td>2.1 - Total classes in trademark applications</td>\n",
" <td>78500.0</td>\n",
" <td>85844.0</td>\n",
" <td>88838.0</td>\n",
" <td>83891.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>3</th>\n",
" <td>Argentina</td>\n",
" <td>2.2 - Share of non-resident trademark class count</td>\n",
" <td>17.9</td>\n",
" <td>18.3</td>\n",
" <td>17.7</td>\n",
" <td>16.5</td>\n",
" </tr>\n",
" <tr>\n",
" <th>4</th>\n",
" <td>Argentina</td>\n",
" <td>3.1 - Total designs in applications</td>\n",
" <td>2099.0</td>\n",
" <td>2372.0</td>\n",
" <td>2230.0</td>\n",
" <td>1932.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>...</th>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" </tr>\n",
" <tr>\n",
" <th>105</th>\n",
" <td>Uruguay</td>\n",
" <td>2.1 - Total classes in trademark applications</td>\n",
" <td>9336.0</td>\n",
" <td>11075.0</td>\n",
" <td>10905.0</td>\n",
" <td>10979.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>106</th>\n",
" <td>Uruguay</td>\n",
" <td>2.2 - Share of non-resident trademark class count</td>\n",
" <td>56.1</td>\n",
" <td>56.3</td>\n",
" <td>55.5</td>\n",
" <td>54.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>107</th>\n",
" <td>Uruguay</td>\n",
" <td>3.1 - Total designs in applications</td>\n",
" <td>83.0</td>\n",
" <td>93.0</td>\n",
" <td>100.0</td>\n",
" <td>164.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>108</th>\n",
" <td>Uruguay</td>\n",
" <td>3.2 - Share of non-resident industrial designs</td>\n",
" <td>60.2</td>\n",
" <td>63.4</td>\n",
" <td>81.0</td>\n",
" <td>73.8</td>\n",
" </tr>\n",
" <tr>\n",
" <th>109</th>\n",
" <td>Uruguay</td>\n",
" <td>4.1 - Utility Model applications</td>\n",
" <td>28.0</td>\n",
" <td>29.0</td>\n",
" <td>31.0</td>\n",
" <td>27.0</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"<p>110 rows × 6 columns</p>\n",
"</div>"
],
"text/plain": [
" Office Statistics 2020 \\\n",
"0 Argentina 1.1 - Patent applications 3492.0 \n",
"1 Argentina 1.2 - Share of non-resident patent applications 73.4 \n",
"2 Argentina 2.1 - Total classes in trademark applications 78500.0 \n",
"3 Argentina 2.2 - Share of non-resident trademark class count 17.9 \n",
"4 Argentina 3.1 - Total designs in applications 2099.0 \n",
".. ... ... ... \n",
"105 Uruguay 2.1 - Total classes in trademark applications 9336.0 \n",
"106 Uruguay 2.2 - Share of non-resident trademark class count 56.1 \n",
"107 Uruguay 3.1 - Total designs in applications 83.0 \n",
"108 Uruguay 3.2 - Share of non-resident industrial designs 60.2 \n",
"109 Uruguay 4.1 - Utility Model applications 28.0 \n",
"\n",
" 2021 2022 2023 \n",
"0 3669.0 3576.0 3418.0 \n",
"1 88.9 87.6 87.7 \n",
"2 85844.0 88838.0 83891.0 \n",
"3 18.3 17.7 16.5 \n",
"4 2372.0 2230.0 1932.0 \n",
".. ... ... ... \n",
"105 11075.0 10905.0 10979.0 \n",
"106 56.3 55.5 54.0 \n",
"107 93.0 100.0 164.0 \n",
"108 63.4 81.0 73.8 \n",
"109 29.0 31.0 27.0 \n",
"\n",
"[110 rows x 6 columns]"
]
},
"execution_count": 21,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"df = pd.read_csv('countryprofiles.csv',index_col=False)\n",
"population_df = pd.read_csv('population.csv',index_col=False)\n",
"df.drop(columns=['2024'], inplace=True)\n",
"df.drop(columns=['Office (Code)'], inplace=True)\n",
"df.drop(columns=['Origin'], inplace=True)\n",
"df"
]
},
{
"cell_type": "code",
"execution_count": 22,
"id": "8d7a7986",
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
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"</style>\n",
"<table border=\"1\" class=\"dataframe\">\n",
" <thead>\n",
" <tr style=\"text-align: right;\">\n",
" <th></th>\n",
" <th>Country Name</th>\n",
" <th>2020</th>\n",
" <th>2021</th>\n",
" <th>2022</th>\n",
" <th>2023</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>0</th>\n",
" <td>Argentina</td>\n",
" <td>45191965</td>\n",
" <td>45312281</td>\n",
" <td>45407904</td>\n",
" <td>45538401</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1</th>\n",
" <td>Belize</td>\n",
" <td>390812</td>\n",
" <td>395346</td>\n",
" <td>402733</td>\n",
" <td>411106</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2</th>\n",
" <td>Bolivia</td>\n",
" <td>11816299</td>\n",
" <td>11937360</td>\n",
" <td>12077154</td>\n",
" <td>12244159</td>\n",
" </tr>\n",
" <tr>\n",
" <th>3</th>\n",
" <td>Brazil</td>\n",
" <td>208660842</td>\n",
" <td>209550294</td>\n",
" <td>210306415</td>\n",
" <td>211140729</td>\n",
" </tr>\n",
" <tr>\n",
" <th>4</th>\n",
" <td>Canada</td>\n",
" <td>38028638</td>\n",
" <td>38239864</td>\n",
" <td>38935934</td>\n",
" <td>40083484</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>"
],
"text/plain": [
" Country Name 2020 2021 2022 2023\n",
"0 Argentina 45191965 45312281 45407904 45538401\n",
"1 Belize 390812 395346 402733 411106\n",
"2 Bolivia 11816299 11937360 12077154 12244159\n",
"3 Brazil 208660842 209550294 210306415 211140729\n",
"4 Canada 38028638 38239864 38935934 40083484"
]
},
"execution_count": 22,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"population_df = population_df[['Country Name','2020','2021','2022','2023']]\n",
"population_df.head()"
]
},
{
"cell_type": "code",
"execution_count": 23,
"id": "b12ea599",
"metadata": {},
"outputs": [
{
"data": {
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"\n",
" .dataframe thead th {\n",
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"</style>\n",
"<table border=\"1\" class=\"dataframe\">\n",
" <thead>\n",
" <tr style=\"text-align: right;\">\n",
" <th></th>\n",
" <th>Office</th>\n",
" <th>Patent_applications_2020</th>\n",
" <th>Patent_applications_2021</th>\n",
" <th>Patent_applications_2022</th>\n",
" <th>Patent_applications_2023</th>\n",
" <th>Share of non-resident patent applications_2020</th>\n",
" <th>Share of non-resident patent applications_2021</th>\n",
" <th>Share of non-resident patent applications_2022</th>\n",
" <th>Share of non-resident patent applications_2023</th>\n",
" <th>Total_classes_in_trademark_applications_2020</th>\n",
" <th>...</th>\n",
" <th>Total_designs_in_applications_2022</th>\n",
" <th>Total_designs_in_applications_2023</th>\n",
" <th>Share of non-resident industrial designs_2020</th>\n",
" <th>Share of non-resident industrial designs_2021</th>\n",
" <th>Share of non-resident industrial designs_2022</th>\n",
" <th>Share of non-resident industrial designs_2023</th>\n",
" <th>Utility_model_applications_2020</th>\n",
" <th>Utility_model_applications_2021</th>\n",
" <th>Utility_model_applications_2022</th>\n",
" <th>Utility_model_applications_2023</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>0</th>\n",
" <td>Argentina</td>\n",
" <td>3492.0</td>\n",
" <td>3669.0</td>\n",
" <td>3576.0</td>\n",
" <td>3418.0</td>\n",
" <td>73.4</td>\n",
" <td>88.9</td>\n",
" <td>87.6</td>\n",
" <td>87.7</td>\n",
" <td>78500.0</td>\n",
" <td>...</td>\n",
" <td>2230.0</td>\n",
" <td>1932.0</td>\n",
" <td>41.0</td>\n",
" <td>37.6</td>\n",
" <td>37.2</td>\n",
" <td>29.2</td>\n",
" <td>201.0</td>\n",
" <td>170.0</td>\n",
" <td>200.0</td>\n",
" <td>167.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1</th>\n",
" <td>Bolivia</td>\n",
" <td>159.0</td>\n",
" <td>232.0</td>\n",
" <td>226.0</td>\n",
" <td>0.0</td>\n",
" <td>95.0</td>\n",
" <td>97.8</td>\n",
" <td>95.6</td>\n",
" <td>0.0</td>\n",
" <td>6593.0</td>\n",
" <td>...</td>\n",
" <td>89.0</td>\n",
" <td>0.0</td>\n",
" <td>55.3</td>\n",
" <td>62.3</td>\n",
" <td>65.2</td>\n",
" <td>0.0</td>\n",
" <td>10.0</td>\n",
" <td>14.0</td>\n",
" <td>10.0</td>\n",
" <td>0.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2</th>\n",
" <td>Brazil</td>\n",
" <td>24338.0</td>\n",
" <td>24232.0</td>\n",
" <td>24759.0</td>\n",
" <td>25369.0</td>\n",
" <td>78.3</td>\n",
" <td>80.7</td>\n",
" <td>82.2</td>\n",
" <td>80.4</td>\n",
" <td>297932.0</td>\n",
" <td>...</td>\n",
" <td>7196.0</td>\n",
" <td>7679.0</td>\n",
" <td>32.0</td>\n",
" <td>32.6</td>\n",
" <td>26.6</td>\n",
" <td>29.7</td>\n",
" <td>2662.0</td>\n",
" <td>2578.0</td>\n",
" <td>2276.0</td>\n",
" <td>2447.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>3</th>\n",
" <td>Canada</td>\n",
" <td>34565.0</td>\n",
" <td>37155.0</td>\n",
" <td>38052.0</td>\n",
" <td>35620.0</td>\n",
" <td>87.1</td>\n",
" <td>87.3</td>\n",
" <td>88.0</td>\n",
" <td>88.5</td>\n",
" <td>147228.0</td>\n",
" <td>...</td>\n",
" <td>8854.0</td>\n",
" <td>9037.0</td>\n",
" <td>90.2</td>\n",
" <td>92.5</td>\n",
" <td>91.8</td>\n",
" <td>91.3</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>4</th>\n",
" <td>Chile</td>\n",
" <td>2805.0</td>\n",
" <td>3082.0</td>\n",
" <td>3136.0</td>\n",
" <td>3251.0</td>\n",
" <td>86.7</td>\n",
" <td>87.0</td>\n",
" <td>88.1</td>\n",
" <td>87.8</td>\n",
" <td>59933.0</td>\n",
" <td>...</td>\n",
" <td>506.0</td>\n",
" <td>452.0</td>\n",
" <td>83.2</td>\n",
" <td>89.2</td>\n",
" <td>89.3</td>\n",
" <td>90.3</td>\n",
" <td>157.0</td>\n",
" <td>113.0</td>\n",
" <td>115.0</td>\n",
" <td>127.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>5</th>\n",
" <td>Colombia</td>\n",
" <td>2121.0</td>\n",
" <td>2287.0</td>\n",
" <td>3032.0</td>\n",
" <td>2012.0</td>\n",
" <td>82.6</td>\n",
" <td>81.1</td>\n",
" <td>63.6</td>\n",
" <td>86.8</td>\n",
" <td>49899.0</td>\n",
" <td>...</td>\n",
" <td>925.0</td>\n",
" <td>950.0</td>\n",
" <td>53.9</td>\n",
" <td>48.9</td>\n",
" <td>47.9</td>\n",
" <td>47.1</td>\n",
" <td>203.0</td>\n",
" <td>145.0</td>\n",
" <td>182.0</td>\n",
" <td>107.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>6</th>\n",
" <td>Costa Rica</td>\n",
" <td>536.0</td>\n",
" <td>581.0</td>\n",
" <td>586.0</td>\n",
" <td>493.0</td>\n",
" <td>97.8</td>\n",
" <td>97.4</td>\n",
" <td>98.5</td>\n",
" <td>96.3</td>\n",
" <td>14663.0</td>\n",
" <td>...</td>\n",
" <td>64.0</td>\n",
" <td>106.0</td>\n",
" <td>88.5</td>\n",
" <td>88.0</td>\n",
" <td>95.3</td>\n",
" <td>91.5</td>\n",
" <td>9.0</td>\n",
" <td>11.0</td>\n",
" <td>5.0</td>\n",
" <td>6.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>7</th>\n",
" <td>El Salvador</td>\n",
" <td>147.0</td>\n",
" <td>146.0</td>\n",
" <td>149.0</td>\n",
" <td>147.0</td>\n",
" <td>97.3</td>\n",
" <td>98.6</td>\n",
" <td>97.3</td>\n",
" <td>93.9</td>\n",
" <td>9302.0</td>\n",
" <td>...</td>\n",
" <td>52.0</td>\n",
" <td>112.0</td>\n",
" <td>73.5</td>\n",
" <td>60.0</td>\n",
" <td>61.5</td>\n",
" <td>18.8</td>\n",
" <td>4.0</td>\n",
" <td>0.0</td>\n",
" <td>2.0</td>\n",
" <td>4.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>8</th>\n",
" <td>Guatemala</td>\n",
" <td>212.0</td>\n",
" <td>258.0</td>\n",
" <td>289.0</td>\n",
" <td>274.0</td>\n",
" <td>96.7</td>\n",
" <td>96.5</td>\n",
" <td>97.6</td>\n",
" <td>98.5</td>\n",
" <td>10409.0</td>\n",
" <td>...</td>\n",
" <td>56.0</td>\n",
" <td>43.0</td>\n",
" <td>95.6</td>\n",
" <td>62.0</td>\n",
" <td>69.6</td>\n",
" <td>81.4</td>\n",
" <td>14.0</td>\n",
" <td>5.0</td>\n",
" <td>5.0</td>\n",
" <td>9.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>9</th>\n",
" <td>Honduras</td>\n",
" <td>161.0</td>\n",
" <td>188.0</td>\n",
" <td>194.0</td>\n",
" <td>167.0</td>\n",
" <td>0.0</td>\n",
" <td>100.0</td>\n",
" <td>100.0</td>\n",
" <td>100.0</td>\n",
" <td>5381.0</td>\n",
" <td>...</td>\n",
" <td>21.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>95.2</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>1.0</td>\n",
" <td>2.0</td>\n",
" <td>0.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>10</th>\n",
" <td>Mexico</td>\n",
" <td>14312.0</td>\n",
" <td>16161.0</td>\n",
" <td>16605.0</td>\n",
" <td>15630.0</td>\n",
" <td>92.1</td>\n",
" <td>93.1</td>\n",
" <td>94.1</td>\n",
" <td>93.7</td>\n",
" <td>162535.0</td>\n",
" <td>...</td>\n",
" <td>4631.0</td>\n",
" <td>4935.0</td>\n",
" <td>72.8</td>\n",
" <td>77.1</td>\n",
" <td>78.0</td>\n",
" <td>78.0</td>\n",
" <td>708.0</td>\n",
" <td>706.0</td>\n",
" <td>608.0</td>\n",
" <td>589.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>11</th>\n",
" <td>Panama</td>\n",
" <td>319.0</td>\n",
" <td>436.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>93.1</td>\n",
" <td>92.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>10982.0</td>\n",
" <td>...</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>100.0</td>\n",
" <td>94.1</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>8.0</td>\n",
" <td>4.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>12</th>\n",
" <td>Paraguay</td>\n",
" <td>337.0</td>\n",
" <td>364.0</td>\n",
" <td>371.0</td>\n",
" <td>344.0</td>\n",
" <td>95.8</td>\n",
" <td>97.3</td>\n",
" <td>98.1</td>\n",
" <td>97.7</td>\n",
" <td>24083.0</td>\n",
" <td>...</td>\n",
" <td>83.0</td>\n",
" <td>110.0</td>\n",
" <td>92.9</td>\n",
" <td>91.0</td>\n",
" <td>98.8</td>\n",
" <td>90.0</td>\n",
" <td>9.0</td>\n",
" <td>15.0</td>\n",
" <td>14.0</td>\n",
" <td>9.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>13</th>\n",
" <td>Peru</td>\n",
" <td>1267.0</td>\n",
" <td>1235.0</td>\n",
" <td>1449.0</td>\n",
" <td>1340.0</td>\n",
" <td>90.1</td>\n",
" <td>92.4</td>\n",
" <td>87.9</td>\n",
" <td>85.9</td>\n",
" <td>37250.0</td>\n",
" <td>...</td>\n",
" <td>391.0</td>\n",
" <td>395.0</td>\n",
" <td>66.3</td>\n",
" <td>75.1</td>\n",
" <td>72.4</td>\n",
" <td>70.9</td>\n",
" <td>416.0</td>\n",
" <td>244.0</td>\n",
" <td>447.0</td>\n",
" <td>634.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>14</th>\n",
" <td>United States of America</td>\n",
" <td>597488.0</td>\n",
" <td>591722.0</td>\n",
" <td>592463.0</td>\n",
" <td>598222.0</td>\n",
" <td>51.8</td>\n",
" <td>52.3</td>\n",
" <td>53.8</td>\n",
" <td>53.5</td>\n",
" <td>870282.0</td>\n",
" <td>...</td>\n",
" <td>56219.0</td>\n",
" <td>60016.0</td>\n",
" <td>57.3</td>\n",
" <td>63.2</td>\n",
" <td>64.6</td>\n",
" <td>67.3</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>15</th>\n",
" <td>Uruguay</td>\n",
" <td>431.0</td>\n",
" <td>558.0</td>\n",
" <td>475.0</td>\n",
" <td>451.0</td>\n",
" <td>94.0</td>\n",
" <td>94.4</td>\n",
" <td>98.7</td>\n",
" <td>96.7</td>\n",
" <td>9336.0</td>\n",
" <td>...</td>\n",
" <td>100.0</td>\n",
" <td>164.0</td>\n",
" <td>60.2</td>\n",
" <td>63.4</td>\n",
" <td>81.0</td>\n",
" <td>73.8</td>\n",
" <td>28.0</td>\n",
" <td>29.0</td>\n",
" <td>31.0</td>\n",
" <td>27.0</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"<p>16 rows × 29 columns</p>\n",
"</div>"
],
"text/plain": [
" Office Patent_applications_2020 \\\n",
"0 Argentina 3492.0 \n",
"1 Bolivia 159.0 \n",
"2 Brazil 24338.0 \n",
"3 Canada 34565.0 \n",
"4 Chile 2805.0 \n",
"5 Colombia 2121.0 \n",
"6 Costa Rica 536.0 \n",
"7 El Salvador 147.0 \n",
"8 Guatemala 212.0 \n",
"9 Honduras 161.0 \n",
"10 Mexico 14312.0 \n",
"11 Panama 319.0 \n",
"12 Paraguay 337.0 \n",
"13 Peru 1267.0 \n",
"14 United States of America 597488.0 \n",
"15 Uruguay 431.0 \n",
"\n",
" Patent_applications_2021 Patent_applications_2022 \\\n",
"0 3669.0 3576.0 \n",
"1 232.0 226.0 \n",
"2 24232.0 24759.0 \n",
"3 37155.0 38052.0 \n",
"4 3082.0 3136.0 \n",
"5 2287.0 3032.0 \n",
"6 581.0 586.0 \n",
"7 146.0 149.0 \n",
"8 258.0 289.0 \n",
"9 188.0 194.0 \n",
"10 16161.0 16605.0 \n",
"11 436.0 0.0 \n",
"12 364.0 371.0 \n",
"13 1235.0 1449.0 \n",
"14 591722.0 592463.0 \n",
"15 558.0 475.0 \n",
"\n",
" Patent_applications_2023 Share of non-resident patent applications_2020 \\\n",
"0 3418.0 73.4 \n",
"1 0.0 95.0 \n",
"2 25369.0 78.3 \n",
"3 35620.0 87.1 \n",
"4 3251.0 86.7 \n",
"5 2012.0 82.6 \n",
"6 493.0 97.8 \n",
"7 147.0 97.3 \n",
"8 274.0 96.7 \n",
"9 167.0 0.0 \n",
"10 15630.0 92.1 \n",
"11 0.0 93.1 \n",
"12 344.0 95.8 \n",
"13 1340.0 90.1 \n",
"14 598222.0 51.8 \n",
"15 451.0 94.0 \n",
"\n",
" Share of non-resident patent applications_2021 \\\n",
"0 88.9 \n",
"1 97.8 \n",
"2 80.7 \n",
"3 87.3 \n",
"4 87.0 \n",
"5 81.1 \n",
"6 97.4 \n",
"7 98.6 \n",
"8 96.5 \n",
"9 100.0 \n",
"10 93.1 \n",
"11 92.0 \n",
"12 97.3 \n",
"13 92.4 \n",
"14 52.3 \n",
"15 94.4 \n",
"\n",
" Share of non-resident patent applications_2022 \\\n",
"0 87.6 \n",
"1 95.6 \n",
"2 82.2 \n",
"3 88.0 \n",
"4 88.1 \n",
"5 63.6 \n",
"6 98.5 \n",
"7 97.3 \n",
"8 97.6 \n",
"9 100.0 \n",
"10 94.1 \n",
"11 0.0 \n",
"12 98.1 \n",
"13 87.9 \n",
"14 53.8 \n",
"15 98.7 \n",
"\n",
" Share of non-resident patent applications_2023 \\\n",
"0 87.7 \n",
"1 0.0 \n",
"2 80.4 \n",
"3 88.5 \n",
"4 87.8 \n",
"5 86.8 \n",
"6 96.3 \n",
"7 93.9 \n",
"8 98.5 \n",
"9 100.0 \n",
"10 93.7 \n",
"11 0.0 \n",
"12 97.7 \n",
"13 85.9 \n",
"14 53.5 \n",
"15 96.7 \n",
"\n",
" Total_classes_in_trademark_applications_2020 ... \\\n",
"0 78500.0 ... \n",
"1 6593.0 ... \n",
"2 297932.0 ... \n",
"3 147228.0 ... \n",
"4 59933.0 ... \n",
"5 49899.0 ... \n",
"6 14663.0 ... \n",
"7 9302.0 ... \n",
"8 10409.0 ... \n",
"9 5381.0 ... \n",
"10 162535.0 ... \n",
"11 10982.0 ... \n",
"12 24083.0 ... \n",
"13 37250.0 ... \n",
"14 870282.0 ... \n",
"15 9336.0 ... \n",
"\n",
" Total_designs_in_applications_2022 Total_designs_in_applications_2023 \\\n",
"0 2230.0 1932.0 \n",
"1 89.0 0.0 \n",
"2 7196.0 7679.0 \n",
"3 8854.0 9037.0 \n",
"4 506.0 452.0 \n",
"5 925.0 950.0 \n",
"6 64.0 106.0 \n",
"7 52.0 112.0 \n",
"8 56.0 43.0 \n",
"9 21.0 0.0 \n",
"10 4631.0 4935.0 \n",
"11 0.0 0.0 \n",
"12 83.0 110.0 \n",
"13 391.0 395.0 \n",
"14 56219.0 60016.0 \n",
"15 100.0 164.0 \n",
"\n",
" Share of non-resident industrial designs_2020 \\\n",
"0 41.0 \n",
"1 55.3 \n",
"2 32.0 \n",
"3 90.2 \n",
"4 83.2 \n",
"5 53.9 \n",
"6 88.5 \n",
"7 73.5 \n",
"8 95.6 \n",
"9 0.0 \n",
"10 72.8 \n",
"11 100.0 \n",
"12 92.9 \n",
"13 66.3 \n",
"14 57.3 \n",
"15 60.2 \n",
"\n",
" Share of non-resident industrial designs_2021 \\\n",
"0 37.6 \n",
"1 62.3 \n",
"2 32.6 \n",
"3 92.5 \n",
"4 89.2 \n",
"5 48.9 \n",
"6 88.0 \n",
"7 60.0 \n",
"8 62.0 \n",
"9 0.0 \n",
"10 77.1 \n",
"11 94.1 \n",
"12 91.0 \n",
"13 75.1 \n",
"14 63.2 \n",
"15 63.4 \n",
"\n",
" Share of non-resident industrial designs_2022 \\\n",
"0 37.2 \n",
"1 65.2 \n",
"2 26.6 \n",
"3 91.8 \n",
"4 89.3 \n",
"5 47.9 \n",
"6 95.3 \n",
"7 61.5 \n",
"8 69.6 \n",
"9 95.2 \n",
"10 78.0 \n",
"11 0.0 \n",
"12 98.8 \n",
"13 72.4 \n",
"14 64.6 \n",
"15 81.0 \n",
"\n",
" Share of non-resident industrial designs_2023 \\\n",
"0 29.2 \n",
"1 0.0 \n",
"2 29.7 \n",
"3 91.3 \n",
"4 90.3 \n",
"5 47.1 \n",
"6 91.5 \n",
"7 18.8 \n",
"8 81.4 \n",
"9 0.0 \n",
"10 78.0 \n",
"11 0.0 \n",
"12 90.0 \n",
"13 70.9 \n",
"14 67.3 \n",
"15 73.8 \n",
"\n",
" Utility_model_applications_2020 Utility_model_applications_2021 \\\n",
"0 201.0 170.0 \n",
"1 10.0 14.0 \n",
"2 2662.0 2578.0 \n",
"3 0.0 0.0 \n",
"4 157.0 113.0 \n",
"5 203.0 145.0 \n",
"6 9.0 11.0 \n",
"7 4.0 0.0 \n",
"8 14.0 5.0 \n",
"9 0.0 1.0 \n",
"10 708.0 706.0 \n",
"11 8.0 4.0 \n",
"12 9.0 15.0 \n",
"13 416.0 244.0 \n",
"14 0.0 0.0 \n",
"15 28.0 29.0 \n",
"\n",
" Utility_model_applications_2022 Utility_model_applications_2023 \n",
"0 200.0 167.0 \n",
"1 10.0 0.0 \n",
"2 2276.0 2447.0 \n",
"3 0.0 0.0 \n",
"4 115.0 127.0 \n",
"5 182.0 107.0 \n",
"6 5.0 6.0 \n",
"7 2.0 4.0 \n",
"8 5.0 9.0 \n",
"9 2.0 0.0 \n",
"10 608.0 589.0 \n",
"11 0.0 0.0 \n",
"12 14.0 9.0 \n",
"13 447.0 634.0 \n",
"14 0.0 0.0 \n",
"15 31.0 27.0 \n",
"\n",
"[16 rows x 29 columns]"
]
},
"execution_count": 23,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"# Using get dummies to convert Statistics to bolean and multiply by 2020, 2021, 2022, 2023\n",
"\n",
"dummies = pd.get_dummies(df, columns=['Statistics'],dtype=int)\n",
"\n",
"# Statistics_1.1 - Patent applications\tStatistics_1.2 - Share of non-resident patent applications\tStatistics_2.1 - Total classes in trademark applications\tStatistics_2.2 - Share of non-resident trademark class count\tStatistics_3.1 - Total designs in applications\tStatistics_3.2 - Share of non-resident industrial designs\tStatistics_4.1 - Utility Model applications\n",
"\n",
"\n",
"dummies['Patent_applications_2020'] = dummies['Statistics_1.1 - Patent applications'] * df['2020']\n",
"dummies['Patent_applications_2021'] = dummies['Statistics_1.1 - Patent applications'] * df['2021']\n",
"dummies['Patent_applications_2022'] = dummies['Statistics_1.1 - Patent applications'] * df['2022']\n",
"dummies['Patent_applications_2023'] = dummies['Statistics_1.1 - Patent applications'] * df['2023']\n",
"dummies.drop(columns=['Statistics_1.1 - Patent applications'], inplace=True)\n",
"\n",
"dummies['Share of non-resident patent applications_2020'] = dummies['Statistics_1.2 - Share of non-resident patent applications'] * df['2020']\n",
"dummies['Share of non-resident patent applications_2021'] = dummies['Statistics_1.2 - Share of non-resident patent applications'] * df['2021']\n",
"dummies['Share of non-resident patent applications_2022'] = dummies['Statistics_1.2 - Share of non-resident patent applications'] * df['2022']\n",
"dummies['Share of non-resident patent applications_2023'] = dummies['Statistics_1.2 - Share of non-resident patent applications'] * df['2023']\n",
"dummies.drop(columns=['Statistics_1.2 - Share of non-resident patent applications'], inplace=True)\n",
"\n",
"# Statistics_2.1 - Total classes in trademark applications\n",
"\n",
"dummies['Total_classes_in_trademark_applications_2020'] = dummies['Statistics_2.1 - Total classes in trademark applications'] * df['2020']\n",
"dummies['Total_classes_in_trademark_applications_2021'] = dummies['Statistics_2.1 - Total classes in trademark applications'] * df['2021']\n",
"dummies['Total_classes_in_trademark_applications_2022'] = dummies['Statistics_2.1 - Total classes in trademark applications'] * df['2022']\n",
"dummies['Total_classes_in_trademark_applications_2023'] = dummies['Statistics_2.1 - Total classes in trademark applications'] * df['2023']\n",
"dummies.drop(columns=['Statistics_2.1 - Total classes in trademark applications'], inplace=True)\n",
"\n",
"# Statistics_2.2 - Share of non-resident trademark class count\n",
"\n",
"dummies['Share of non-resident trademark class count_2020'] = dummies['Statistics_2.2 - Share of non-resident trademark class count'] * df['2020']\n",
"dummies['Share of non-resident trademark class count_2021'] = dummies['Statistics_2.2 - Share of non-resident trademark class count'] * df['2021']\n",
"dummies['Share of non-resident trademark class count_2022'] = dummies['Statistics_2.2 - Share of non-resident trademark class count'] * df['2022']\n",
"dummies['Share of non-resident trademark class count_2023'] = dummies['Statistics_2.2 - Share of non-resident trademark class count'] * df['2023']\n",
"dummies.drop(columns=['Statistics_2.2 - Share of non-resident trademark class count'], inplace=True)\n",
"\n",
"# Statistics_3.1 - Total designs in applications\n",
"\n",
"dummies['Total_designs_in_applications_2020'] = dummies['Statistics_3.1 - Total designs in applications'] * df['2020']\n",
"dummies['Total_designs_in_applications_2021'] = dummies['Statistics_3.1 - Total designs in applications'] * df['2021']\n",
"dummies['Total_designs_in_applications_2022'] = dummies['Statistics_3.1 - Total designs in applications'] * df['2022']\n",
"dummies['Total_designs_in_applications_2023'] = dummies['Statistics_3.1 - Total designs in applications'] * df['2023']\n",
"dummies.drop(columns=['Statistics_3.1 - Total designs in applications'], inplace=True)\n",
"\n",
"# Statistics_3.2 - Share of non-resident industrial designs\n",
"\n",
"dummies['Share of non-resident industrial designs_2020'] = dummies['Statistics_3.2 - Share of non-resident industrial designs'] * df['2020']\n",
"dummies['Share of non-resident industrial designs_2021'] = dummies['Statistics_3.2 - Share of non-resident industrial designs'] * df['2021']\n",
"dummies['Share of non-resident industrial designs_2022'] = dummies['Statistics_3.2 - Share of non-resident industrial designs'] * df['2022']\n",
"dummies['Share of non-resident industrial designs_2023'] = dummies['Statistics_3.2 - Share of non-resident industrial designs'] * df['2023']\n",
"dummies.drop(columns=['Statistics_3.2 - Share of non-resident industrial designs'], inplace=True)\n",
"\n",
"# Statistics_4.1 - Utility Model applications\n",
"\n",
"dummies['Utility_model_applications_2020'] = dummies['Statistics_4.1 - Utility Model applications'] * df['2020']\n",
"dummies['Utility_model_applications_2021'] = dummies['Statistics_4.1 - Utility Model applications'] * df['2021']\n",
"dummies['Utility_model_applications_2022'] = dummies['Statistics_4.1 - Utility Model applications'] * df['2022']\n",
"dummies['Utility_model_applications_2023'] = dummies['Statistics_4.1 - Utility Model applications'] * df['2023']\n",
"dummies.drop(columns=['Statistics_4.1 - Utility Model applications'], inplace=True)\n",
"\n",
"dummies.drop(columns=['2020','2021','2022','2023'], inplace=True)\n",
"\n",
"# df.groupby('ID')[['Category_A', 'Category_B']].sum().reset_index()\n",
"\n",
"sparsed_df = dummies.groupby('Office').sum()\n",
"\n",
"sparsed_df.reset_index(inplace=True)\n",
"sparsed_df\n"
]
},
{
"cell_type": "code",
"execution_count": 37,
"id": "faefb705",
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
"<div>\n",
"<style scoped>\n",
" .dataframe tbody tr th:only-of-type {\n",
" vertical-align: middle;\n",
" }\n",
"\n",
" .dataframe tbody tr th {\n",
" vertical-align: top;\n",
" }\n",
"\n",
" .dataframe thead th {\n",
" text-align: right;\n",
" }\n",
"</style>\n",
"<table border=\"1\" class=\"dataframe\">\n",
" <thead>\n",
" <tr style=\"text-align: right;\">\n",
" <th></th>\n",
" <th>Office</th>\n",
" <th>Patent_applications_2020</th>\n",
" <th>Patent_applications_2021</th>\n",
" <th>Patent_applications_2022</th>\n",
" <th>Patent_applications_2023</th>\n",
" <th>Share of non-resident patent applications_2020</th>\n",
" <th>Share of non-resident patent applications_2021</th>\n",
" <th>Share of non-resident patent applications_2022</th>\n",
" <th>Share of non-resident patent applications_2023</th>\n",
" <th>Total_classes_in_trademark_applications_2020</th>\n",
" <th>...</th>\n",
" <th>2022</th>\n",
" <th>2023</th>\n",
" <th>per_capita_2020</th>\n",
" <th>per_capita_2021</th>\n",
" <th>per_capita_2022</th>\n",
" <th>per_capita_2023</th>\n",
" <th>Total_population</th>\n",
" <th>Total_patents</th>\n",
" <th>per_capita_Total_patents</th>\n",
" <th>patents_per_million_population</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>14</th>\n",
" <td>United States of America</td>\n",
" <td>597488.0</td>\n",
" <td>591722.0</td>\n",
" <td>592463.0</td>\n",
" <td>598222.0</td>\n",
" <td>51.8</td>\n",
" <td>52.3</td>\n",
" <td>53.8</td>\n",
" <td>53.5</td>\n",
" <td>870282.0</td>\n",
" <td>...</td>\n",
" <td>334017321</td>\n",
" <td>336806231</td>\n",
" <td>0.001802</td>\n",
" <td>0.001782</td>\n",
" <td>0.001774</td>\n",
" <td>0.001776</td>\n",
" <td>1334501032</td>\n",
" <td>2379895.0</td>\n",
" <td>0.001783</td>\n",
" <td>1783.36</td>\n",
" </tr>\n",
" <tr>\n",
" <th>3</th>\n",
" <td>Canada</td>\n",
" <td>34565.0</td>\n",
" <td>37155.0</td>\n",
" <td>38052.0</td>\n",
" <td>35620.0</td>\n",
" <td>87.1</td>\n",
" <td>87.3</td>\n",
" <td>88.0</td>\n",
" <td>88.5</td>\n",
" <td>147228.0</td>\n",
" <td>...</td>\n",
" <td>38935934</td>\n",
" <td>40083484</td>\n",
" <td>0.000909</td>\n",
" <td>0.000972</td>\n",
" <td>0.000977</td>\n",
" <td>0.000889</td>\n",
" <td>155287920</td>\n",
" <td>145392.0</td>\n",
" <td>0.000936</td>\n",
" <td>936.27</td>\n",
" </tr>\n",
" <tr>\n",
" <th>4</th>\n",
" <td>Chile</td>\n",
" <td>2805.0</td>\n",
" <td>3082.0</td>\n",
" <td>3136.0</td>\n",
" <td>3251.0</td>\n",
" <td>86.7</td>\n",
" <td>87.0</td>\n",
" <td>88.1</td>\n",
" <td>87.8</td>\n",
" <td>59933.0</td>\n",
" <td>...</td>\n",
" <td>19553036</td>\n",
" <td>19658835</td>\n",
" <td>0.000145</td>\n",
" <td>0.000158</td>\n",
" <td>0.000160</td>\n",
" <td>0.000165</td>\n",
" <td>78038829</td>\n",
" <td>12274.0</td>\n",
" <td>0.000157</td>\n",
" <td>157.28</td>\n",
" </tr>\n",
" <tr>\n",
" <th>15</th>\n",
" <td>Uruguay</td>\n",
" <td>431.0</td>\n",
" <td>558.0</td>\n",
" <td>475.0</td>\n",
" <td>451.0</td>\n",
" <td>94.0</td>\n",
" <td>94.4</td>\n",
" <td>98.7</td>\n",
" <td>96.7</td>\n",
" <td>9336.0</td>\n",
" <td>...</td>\n",
" <td>3390913</td>\n",
" <td>3388081</td>\n",
" <td>0.000127</td>\n",
" <td>0.000164</td>\n",
" <td>0.000140</td>\n",
" <td>0.000133</td>\n",
" <td>13574657</td>\n",
" <td>1915.0</td>\n",
" <td>0.000141</td>\n",
" <td>141.07</td>\n",
" </tr>\n",
" <tr>\n",
" <th>10</th>\n",
" <td>Mexico</td>\n",
" <td>14312.0</td>\n",
" <td>16161.0</td>\n",
" <td>16605.0</td>\n",
" <td>15630.0</td>\n",
" <td>92.1</td>\n",
" <td>93.1</td>\n",
" <td>94.1</td>\n",
" <td>93.7</td>\n",
" <td>162535.0</td>\n",
" <td>...</td>\n",
" <td>128613117</td>\n",
" <td>129739759</td>\n",
" <td>0.000113</td>\n",
" <td>0.000127</td>\n",
" <td>0.000129</td>\n",
" <td>0.000120</td>\n",
" <td>512800078</td>\n",
" <td>62708.0</td>\n",
" <td>0.000122</td>\n",
" <td>122.29</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2</th>\n",
" <td>Brazil</td>\n",
" <td>24338.0</td>\n",
" <td>24232.0</td>\n",
" <td>24759.0</td>\n",
" <td>25369.0</td>\n",
" <td>78.3</td>\n",
" <td>80.7</td>\n",
" <td>82.2</td>\n",
" <td>80.4</td>\n",
" <td>297932.0</td>\n",
" <td>...</td>\n",
" <td>210306415</td>\n",
" <td>211140729</td>\n",
" <td>0.000117</td>\n",
" <td>0.000116</td>\n",
" <td>0.000118</td>\n",
" <td>0.000120</td>\n",
" <td>839658280</td>\n",
" <td>98698.0</td>\n",
" <td>0.000118</td>\n",
" <td>117.55</td>\n",
" </tr>\n",
" <tr>\n",
" <th>6</th>\n",
" <td>Costa Rica</td>\n",
" <td>536.0</td>\n",
" <td>581.0</td>\n",
" <td>586.0</td>\n",
" <td>493.0</td>\n",
" <td>97.8</td>\n",
" <td>97.4</td>\n",
" <td>98.5</td>\n",
" <td>96.3</td>\n",
" <td>14663.0</td>\n",
" <td>...</td>\n",
" <td>5081765</td>\n",
" <td>5105525</td>\n",
" <td>0.000106</td>\n",
" <td>0.000115</td>\n",
" <td>0.000115</td>\n",
" <td>0.000097</td>\n",
" <td>20281598</td>\n",
" <td>2196.0</td>\n",
" <td>0.000108</td>\n",
" <td>108.28</td>\n",
" </tr>\n",
" <tr>\n",
" <th>0</th>\n",
" <td>Argentina</td>\n",
" <td>3492.0</td>\n",
" <td>3669.0</td>\n",
" <td>3576.0</td>\n",
" <td>3418.0</td>\n",
" <td>73.4</td>\n",
" <td>88.9</td>\n",
" <td>87.6</td>\n",
" <td>87.7</td>\n",
" <td>78500.0</td>\n",
" <td>...</td>\n",
" <td>45407904</td>\n",
" <td>45538401</td>\n",
" <td>0.000077</td>\n",
" <td>0.000081</td>\n",
" <td>0.000079</td>\n",
" <td>0.000075</td>\n",
" <td>181450551</td>\n",
" <td>14155.0</td>\n",
" <td>0.000078</td>\n",
" <td>78.01</td>\n",
" </tr>\n",
" <tr>\n",
" <th>12</th>\n",
" <td>Paraguay</td>\n",
" <td>337.0</td>\n",
" <td>364.0</td>\n",
" <td>371.0</td>\n",
" <td>344.0</td>\n",
" <td>95.8</td>\n",
" <td>97.3</td>\n",
" <td>98.1</td>\n",
" <td>97.7</td>\n",
" <td>24083.0</td>\n",
" <td>...</td>\n",
" <td>6760464</td>\n",
" <td>6844146</td>\n",
" <td>0.000051</td>\n",
" <td>0.000054</td>\n",
" <td>0.000055</td>\n",
" <td>0.000050</td>\n",
" <td>26892531</td>\n",
" <td>1416.0</td>\n",
" <td>0.000053</td>\n",
" <td>52.65</td>\n",
" </tr>\n",
" <tr>\n",
" <th>5</th>\n",
" <td>Colombia</td>\n",
" <td>2121.0</td>\n",
" <td>2287.0</td>\n",
" <td>3032.0</td>\n",
" <td>2012.0</td>\n",
" <td>82.6</td>\n",
" <td>81.1</td>\n",
" <td>63.6</td>\n",
" <td>86.8</td>\n",
" <td>49899.0</td>\n",
" <td>...</td>\n",
" <td>51737944</td>\n",
" <td>52321152</td>\n",
" <td>0.000042</td>\n",
" <td>0.000045</td>\n",
" <td>0.000059</td>\n",
" <td>0.000038</td>\n",
" <td>205877266</td>\n",
" <td>9452.0</td>\n",
" <td>0.000046</td>\n",
" <td>45.91</td>\n",
" </tr>\n",
" <tr>\n",
" <th>11</th>\n",
" <td>Panama</td>\n",
" <td>319.0</td>\n",
" <td>436.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>93.1</td>\n",
" <td>92.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>10982.0</td>\n",
" <td>...</td>\n",
" <td>4400773</td>\n",
" <td>4458759</td>\n",
" <td>0.000074</td>\n",
" <td>0.000100</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>17498198</td>\n",
" <td>755.0</td>\n",
" <td>0.000043</td>\n",
" <td>43.15</td>\n",
" </tr>\n",
" <tr>\n",
" <th>13</th>\n",
" <td>Peru</td>\n",
" <td>1267.0</td>\n",
" <td>1235.0</td>\n",
" <td>1449.0</td>\n",
" <td>1340.0</td>\n",
" <td>90.1</td>\n",
" <td>92.4</td>\n",
" <td>87.9</td>\n",
" <td>85.9</td>\n",
" <td>37250.0</td>\n",
" <td>...</td>\n",
" <td>33475438</td>\n",
" <td>33845617</td>\n",
" <td>0.000039</td>\n",
" <td>0.000037</td>\n",
" <td>0.000043</td>\n",
" <td>0.000040</td>\n",
" <td>133315516</td>\n",
" <td>5291.0</td>\n",
" <td>0.000040</td>\n",
" <td>39.69</td>\n",
" </tr>\n",
" <tr>\n",
" <th>7</th>\n",
" <td>El Salvador</td>\n",
" <td>147.0</td>\n",
" <td>146.0</td>\n",
" <td>149.0</td>\n",
" <td>147.0</td>\n",
" <td>97.3</td>\n",
" <td>98.6</td>\n",
" <td>97.3</td>\n",
" <td>93.9</td>\n",
" <td>9302.0</td>\n",
" <td>...</td>\n",
" <td>6280319</td>\n",
" <td>6309624</td>\n",
" <td>0.000024</td>\n",
" <td>0.000023</td>\n",
" <td>0.000024</td>\n",
" <td>0.000023</td>\n",
" <td>25080398</td>\n",
" <td>589.0</td>\n",
" <td>0.000023</td>\n",
" <td>23.48</td>\n",
" </tr>\n",
" <tr>\n",
" <th>9</th>\n",
" <td>Honduras</td>\n",
" <td>161.0</td>\n",
" <td>188.0</td>\n",
" <td>194.0</td>\n",
" <td>167.0</td>\n",
" <td>0.0</td>\n",
" <td>100.0</td>\n",
" <td>100.0</td>\n",
" <td>100.0</td>\n",
" <td>5381.0</td>\n",
" <td>...</td>\n",
" <td>10463872</td>\n",
" <td>10644851</td>\n",
" <td>0.000016</td>\n",
" <td>0.000018</td>\n",
" <td>0.000019</td>\n",
" <td>0.000016</td>\n",
" <td>41518240</td>\n",
" <td>710.0</td>\n",
" <td>0.000017</td>\n",
" <td>17.10</td>\n",
" </tr>\n",
" <tr>\n",
" <th>8</th>\n",
" <td>Guatemala</td>\n",
" <td>212.0</td>\n",
" <td>258.0</td>\n",
" <td>289.0</td>\n",
" <td>274.0</td>\n",
" <td>96.7</td>\n",
" <td>96.5</td>\n",
" <td>97.6</td>\n",
" <td>98.5</td>\n",
" <td>10409.0</td>\n",
" <td>...</td>\n",
" <td>17847877</td>\n",
" <td>18124838</td>\n",
" <td>0.000012</td>\n",
" <td>0.000015</td>\n",
" <td>0.000016</td>\n",
" <td>0.000015</td>\n",
" <td>70928690</td>\n",
" <td>1033.0</td>\n",
" <td>0.000015</td>\n",
" <td>14.56</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1</th>\n",
" <td>Bolivia</td>\n",
" <td>159.0</td>\n",
" <td>232.0</td>\n",
" <td>226.0</td>\n",
" <td>0.0</td>\n",
" <td>95.0</td>\n",
" <td>97.8</td>\n",
" <td>95.6</td>\n",
" <td>0.0</td>\n",
" <td>6593.0</td>\n",
" <td>...</td>\n",
" <td>12077154</td>\n",
" <td>12244159</td>\n",
" <td>0.000013</td>\n",
" <td>0.000019</td>\n",
" <td>0.000019</td>\n",
" <td>0.000000</td>\n",
" <td>48074972</td>\n",
" <td>617.0</td>\n",
" <td>0.000013</td>\n",
" <td>12.83</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"<p>16 rows × 42 columns</p>\n",
"</div>"
],
"text/plain": [
" Office Patent_applications_2020 \\\n",
"14 United States of America 597488.0 \n",
"3 Canada 34565.0 \n",
"4 Chile 2805.0 \n",
"15 Uruguay 431.0 \n",
"10 Mexico 14312.0 \n",
"2 Brazil 24338.0 \n",
"6 Costa Rica 536.0 \n",
"0 Argentina 3492.0 \n",
"12 Paraguay 337.0 \n",
"5 Colombia 2121.0 \n",
"11 Panama 319.0 \n",
"13 Peru 1267.0 \n",
"7 El Salvador 147.0 \n",
"9 Honduras 161.0 \n",
"8 Guatemala 212.0 \n",
"1 Bolivia 159.0 \n",
"\n",
" Patent_applications_2021 Patent_applications_2022 \\\n",
"14 591722.0 592463.0 \n",
"3 37155.0 38052.0 \n",
"4 3082.0 3136.0 \n",
"15 558.0 475.0 \n",
"10 16161.0 16605.0 \n",
"2 24232.0 24759.0 \n",
"6 581.0 586.0 \n",
"0 3669.0 3576.0 \n",
"12 364.0 371.0 \n",
"5 2287.0 3032.0 \n",
"11 436.0 0.0 \n",
"13 1235.0 1449.0 \n",
"7 146.0 149.0 \n",
"9 188.0 194.0 \n",
"8 258.0 289.0 \n",
"1 232.0 226.0 \n",
"\n",
" Patent_applications_2023 Share of non-resident patent applications_2020 \\\n",
"14 598222.0 51.8 \n",
"3 35620.0 87.1 \n",
"4 3251.0 86.7 \n",
"15 451.0 94.0 \n",
"10 15630.0 92.1 \n",
"2 25369.0 78.3 \n",
"6 493.0 97.8 \n",
"0 3418.0 73.4 \n",
"12 344.0 95.8 \n",
"5 2012.0 82.6 \n",
"11 0.0 93.1 \n",
"13 1340.0 90.1 \n",
"7 147.0 97.3 \n",
"9 167.0 0.0 \n",
"8 274.0 96.7 \n",
"1 0.0 95.0 \n",
"\n",
" Share of non-resident patent applications_2021 \\\n",
"14 52.3 \n",
"3 87.3 \n",
"4 87.0 \n",
"15 94.4 \n",
"10 93.1 \n",
"2 80.7 \n",
"6 97.4 \n",
"0 88.9 \n",
"12 97.3 \n",
"5 81.1 \n",
"11 92.0 \n",
"13 92.4 \n",
"7 98.6 \n",
"9 100.0 \n",
"8 96.5 \n",
"1 97.8 \n",
"\n",
" Share of non-resident patent applications_2022 \\\n",
"14 53.8 \n",
"3 88.0 \n",
"4 88.1 \n",
"15 98.7 \n",
"10 94.1 \n",
"2 82.2 \n",
"6 98.5 \n",
"0 87.6 \n",
"12 98.1 \n",
"5 63.6 \n",
"11 0.0 \n",
"13 87.9 \n",
"7 97.3 \n",
"9 100.0 \n",
"8 97.6 \n",
"1 95.6 \n",
"\n",
" Share of non-resident patent applications_2023 \\\n",
"14 53.5 \n",
"3 88.5 \n",
"4 87.8 \n",
"15 96.7 \n",
"10 93.7 \n",
"2 80.4 \n",
"6 96.3 \n",
"0 87.7 \n",
"12 97.7 \n",
"5 86.8 \n",
"11 0.0 \n",
"13 85.9 \n",
"7 93.9 \n",
"9 100.0 \n",
"8 98.5 \n",
"1 0.0 \n",
"\n",
" Total_classes_in_trademark_applications_2020 ... 2022 2023 \\\n",
"14 870282.0 ... 334017321 336806231 \n",
"3 147228.0 ... 38935934 40083484 \n",
"4 59933.0 ... 19553036 19658835 \n",
"15 9336.0 ... 3390913 3388081 \n",
"10 162535.0 ... 128613117 129739759 \n",
"2 297932.0 ... 210306415 211140729 \n",
"6 14663.0 ... 5081765 5105525 \n",
"0 78500.0 ... 45407904 45538401 \n",
"12 24083.0 ... 6760464 6844146 \n",
"5 49899.0 ... 51737944 52321152 \n",
"11 10982.0 ... 4400773 4458759 \n",
"13 37250.0 ... 33475438 33845617 \n",
"7 9302.0 ... 6280319 6309624 \n",
"9 5381.0 ... 10463872 10644851 \n",
"8 10409.0 ... 17847877 18124838 \n",
"1 6593.0 ... 12077154 12244159 \n",
"\n",
" per_capita_2020 per_capita_2021 per_capita_2022 per_capita_2023 \\\n",
"14 0.001802 0.001782 0.001774 0.001776 \n",
"3 0.000909 0.000972 0.000977 0.000889 \n",
"4 0.000145 0.000158 0.000160 0.000165 \n",
"15 0.000127 0.000164 0.000140 0.000133 \n",
"10 0.000113 0.000127 0.000129 0.000120 \n",
"2 0.000117 0.000116 0.000118 0.000120 \n",
"6 0.000106 0.000115 0.000115 0.000097 \n",
"0 0.000077 0.000081 0.000079 0.000075 \n",
"12 0.000051 0.000054 0.000055 0.000050 \n",
"5 0.000042 0.000045 0.000059 0.000038 \n",
"11 0.000074 0.000100 0.000000 0.000000 \n",
"13 0.000039 0.000037 0.000043 0.000040 \n",
"7 0.000024 0.000023 0.000024 0.000023 \n",
"9 0.000016 0.000018 0.000019 0.000016 \n",
"8 0.000012 0.000015 0.000016 0.000015 \n",
"1 0.000013 0.000019 0.000019 0.000000 \n",
"\n",
" Total_population Total_patents per_capita_Total_patents \\\n",
"14 1334501032 2379895.0 0.001783 \n",
"3 155287920 145392.0 0.000936 \n",
"4 78038829 12274.0 0.000157 \n",
"15 13574657 1915.0 0.000141 \n",
"10 512800078 62708.0 0.000122 \n",
"2 839658280 98698.0 0.000118 \n",
"6 20281598 2196.0 0.000108 \n",
"0 181450551 14155.0 0.000078 \n",
"12 26892531 1416.0 0.000053 \n",
"5 205877266 9452.0 0.000046 \n",
"11 17498198 755.0 0.000043 \n",
"13 133315516 5291.0 0.000040 \n",
"7 25080398 589.0 0.000023 \n",
"9 41518240 710.0 0.000017 \n",
"8 70928690 1033.0 0.000015 \n",
"1 48074972 617.0 0.000013 \n",
"\n",
" patents_per_million_population \n",
"14 1783.36 \n",
"3 936.27 \n",
"4 157.28 \n",
"15 141.07 \n",
"10 122.29 \n",
"2 117.55 \n",
"6 108.28 \n",
"0 78.01 \n",
"12 52.65 \n",
"5 45.91 \n",
"11 43.15 \n",
"13 39.69 \n",
"7 23.48 \n",
"9 17.10 \n",
"8 14.56 \n",
"1 12.83 \n",
"\n",
"[16 rows x 42 columns]"
]
},
"execution_count": 37,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"# Join both dataframes. pupulation by \"country Name\" is \"Office\" for the df\n",
"merged = pd.merge(sparsed_df, population_df, left_on='Office', right_on='Country Name', how='left', suffixes=('', ' Population'))\n",
"\n",
"merged['per_capita_2020'] = merged['Patent_applications_2020'] / merged['2020']\n",
"merged['per_capita_2021'] = merged['Patent_applications_2021'] / merged['2021']\n",
"merged['per_capita_2022'] = merged['Patent_applications_2022'] / merged['2022']\n",
"merged['per_capita_2023'] = merged['Patent_applications_2023'] / merged['2023']\n",
"\n",
"merged['Total_population'] = merged['2020'] + merged['2021'] + merged['2022'] + merged['2023']\n",
"merged['Total_patents'] = merged['Patent_applications_2020'] + merged['Patent_applications_2021'] + merged['Patent_applications_2022'] + merged['Patent_applications_2023']\n",
"merged['per_capita_Total_patents'] = merged['Total_patents'] / merged['Total_population']\n",
"\n",
"merged['patents_per_million_population'] = np.round(merged['Total_patents'] / merged['Total_population'] * 1000000,2)\n",
"\n",
"merged.sort_values(by='per_capita_Total_patents', ascending=False,inplace=True)\n",
"merged"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "377997b0",
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
"<div>\n",
"<style scoped>\n",
" .dataframe tbody tr th:only-of-type {\n",
" vertical-align: middle;\n",
" }\n",
"\n",
" .dataframe tbody tr th {\n",
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" }\n",
"\n",
" .dataframe thead th {\n",
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"</style>\n",
"<table border=\"1\" class=\"dataframe\">\n",
" <thead>\n",
" <tr style=\"text-align: right;\">\n",
" <th></th>\n",
" <th>Office</th>\n",
" <th>Total_patents</th>\n",
" <th>patents_per_million_population</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>14</th>\n",
" <td>United States of America</td>\n",
" <td>2379895.0</td>\n",
" <td>1783.36</td>\n",
" </tr>\n",
" <tr>\n",
" <th>3</th>\n",
" <td>Canada</td>\n",
" <td>145392.0</td>\n",
" <td>936.27</td>\n",
" </tr>\n",
" <tr>\n",
" <th>4</th>\n",
" <td>Chile</td>\n",
" <td>12274.0</td>\n",
" <td>157.28</td>\n",
" </tr>\n",
" <tr>\n",
" <th>15</th>\n",
" <td>Uruguay</td>\n",
" <td>1915.0</td>\n",
" <td>141.07</td>\n",
" </tr>\n",
" <tr>\n",
" <th>10</th>\n",
" <td>Mexico</td>\n",
" <td>62708.0</td>\n",
" <td>122.29</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2</th>\n",
" <td>Brazil</td>\n",
" <td>98698.0</td>\n",
" <td>117.55</td>\n",
" </tr>\n",
" <tr>\n",
" <th>6</th>\n",
" <td>Costa Rica</td>\n",
" <td>2196.0</td>\n",
" <td>108.28</td>\n",
" </tr>\n",
" <tr>\n",
" <th>0</th>\n",
" <td>Argentina</td>\n",
" <td>14155.0</td>\n",
" <td>78.01</td>\n",
" </tr>\n",
" <tr>\n",
" <th>12</th>\n",
" <td>Paraguay</td>\n",
" <td>1416.0</td>\n",
" <td>52.65</td>\n",
" </tr>\n",
" <tr>\n",
" <th>5</th>\n",
" <td>Colombia</td>\n",
" <td>9452.0</td>\n",
" <td>45.91</td>\n",
" </tr>\n",
" <tr>\n",
" <th>11</th>\n",
" <td>Panama</td>\n",
" <td>755.0</td>\n",
" <td>43.15</td>\n",
" </tr>\n",
" <tr>\n",
" <th>13</th>\n",
" <td>Peru</td>\n",
" <td>5291.0</td>\n",
" <td>39.69</td>\n",
" </tr>\n",
" <tr>\n",
" <th>7</th>\n",
" <td>El Salvador</td>\n",
" <td>589.0</td>\n",
" <td>23.48</td>\n",
" </tr>\n",
" <tr>\n",
" <th>9</th>\n",
" <td>Honduras</td>\n",
" <td>710.0</td>\n",
" <td>17.10</td>\n",
" </tr>\n",
" <tr>\n",
" <th>8</th>\n",
" <td>Guatemala</td>\n",
" <td>1033.0</td>\n",
" <td>14.56</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1</th>\n",
" <td>Bolivia</td>\n",
" <td>617.0</td>\n",
" <td>12.83</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>"
],
"text/plain": [
" Office Total_patents patents_per_million_population\n",
"14 United States of America 2379895.0 1783.36\n",
"3 Canada 145392.0 936.27\n",
"4 Chile 12274.0 157.28\n",
"15 Uruguay 1915.0 141.07\n",
"10 Mexico 62708.0 122.29\n",
"2 Brazil 98698.0 117.55\n",
"6 Costa Rica 2196.0 108.28\n",
"0 Argentina 14155.0 78.01\n",
"12 Paraguay 1416.0 52.65\n",
"5 Colombia 9452.0 45.91\n",
"11 Panama 755.0 43.15\n",
"13 Peru 5291.0 39.69\n",
"7 El Salvador 589.0 23.48\n",
"9 Honduras 710.0 17.10\n",
"8 Guatemala 1033.0 14.56\n",
"1 Bolivia 617.0 12.83"
]
},
"execution_count": 39,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"article_df = merged[['Office','Total_patents','patents_per_million_population']][:20]"
]
},
{
"cell_type": "code",
"execution_count": 41,
"id": "1a66afd6",
"metadata": {},
"outputs": [],
"source": [
"article_df.to_csv('article_data.csv', index=False)"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "113d8b28",
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
"<div>\n",
"<style scoped>\n",
" .dataframe tbody tr th:only-of-type {\n",
" vertical-align: middle;\n",
" }\n",
"\n",
" .dataframe tbody tr th {\n",
" vertical-align: top;\n",
" }\n",
"\n",
" .dataframe thead th {\n",
" text-align: right;\n",
" }\n",
"</style>\n",
"<table border=\"1\" class=\"dataframe\">\n",
" <thead>\n",
" <tr style=\"text-align: right;\">\n",
" <th></th>\n",
" <th>Office</th>\n",
" <th>2020</th>\n",
" <th>2021</th>\n",
" <th>2022</th>\n",
" <th>2023</th>\n",
" <th>Total</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>14</th>\n",
" <td>United States of America</td>\n",
" <td>597488.0</td>\n",
" <td>591722.0</td>\n",
" <td>592463.0</td>\n",
" <td>598222.0</td>\n",
" <td>2379895.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>3</th>\n",
" <td>Canada</td>\n",
" <td>34565.0</td>\n",
" <td>37155.0</td>\n",
" <td>38052.0</td>\n",
" <td>35620.0</td>\n",
" <td>145392.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2</th>\n",
" <td>Brazil</td>\n",
" <td>24338.0</td>\n",
" <td>24232.0</td>\n",
" <td>24759.0</td>\n",
" <td>25369.0</td>\n",
" <td>98698.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>10</th>\n",
" <td>Mexico</td>\n",
" <td>14312.0</td>\n",
" <td>16161.0</td>\n",
" <td>16605.0</td>\n",
" <td>15630.0</td>\n",
" <td>62708.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>0</th>\n",
" <td>Argentina</td>\n",
" <td>3492.0</td>\n",
" <td>3669.0</td>\n",
" <td>3576.0</td>\n",
" <td>3418.0</td>\n",
" <td>14155.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>4</th>\n",
" <td>Chile</td>\n",
" <td>2805.0</td>\n",
" <td>3082.0</td>\n",
" <td>3136.0</td>\n",
" <td>3251.0</td>\n",
" <td>12274.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>5</th>\n",
" <td>Colombia</td>\n",
" <td>2121.0</td>\n",
" <td>2287.0</td>\n",
" <td>3032.0</td>\n",
" <td>2012.0</td>\n",
" <td>9452.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>13</th>\n",
" <td>Peru</td>\n",
" <td>1267.0</td>\n",
" <td>1235.0</td>\n",
" <td>1449.0</td>\n",
" <td>1340.0</td>\n",
" <td>5291.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>6</th>\n",
" <td>Costa Rica</td>\n",
" <td>536.0</td>\n",
" <td>581.0</td>\n",
" <td>586.0</td>\n",
" <td>493.0</td>\n",
" <td>2196.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>15</th>\n",
" <td>Uruguay</td>\n",
" <td>431.0</td>\n",
" <td>558.0</td>\n",
" <td>475.0</td>\n",
" <td>451.0</td>\n",
" <td>1915.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>12</th>\n",
" <td>Paraguay</td>\n",
" <td>337.0</td>\n",
" <td>364.0</td>\n",
" <td>371.0</td>\n",
" <td>344.0</td>\n",
" <td>1416.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>8</th>\n",
" <td>Guatemala</td>\n",
" <td>212.0</td>\n",
" <td>258.0</td>\n",
" <td>289.0</td>\n",
" <td>274.0</td>\n",
" <td>1033.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>11</th>\n",
" <td>Panama</td>\n",
" <td>319.0</td>\n",
" <td>436.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>755.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>9</th>\n",
" <td>Honduras</td>\n",
" <td>161.0</td>\n",
" <td>188.0</td>\n",
" <td>194.0</td>\n",
" <td>167.0</td>\n",
" <td>710.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1</th>\n",
" <td>Bolivia (Plurinational State of)</td>\n",
" <td>159.0</td>\n",
" <td>232.0</td>\n",
" <td>226.0</td>\n",
" <td>0.0</td>\n",
" <td>617.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>7</th>\n",
" <td>El Salvador</td>\n",
" <td>147.0</td>\n",
" <td>146.0</td>\n",
" <td>149.0</td>\n",
" <td>147.0</td>\n",
" <td>589.0</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>"
],
"text/plain": [
" Office 2020 2021 2022 2023 \\\n",
"14 United States of America 597488.0 591722.0 592463.0 598222.0 \n",
"3 Canada 34565.0 37155.0 38052.0 35620.0 \n",
"2 Brazil 24338.0 24232.0 24759.0 25369.0 \n",
"10 Mexico 14312.0 16161.0 16605.0 15630.0 \n",
"0 Argentina 3492.0 3669.0 3576.0 3418.0 \n",
"4 Chile 2805.0 3082.0 3136.0 3251.0 \n",
"5 Colombia 2121.0 2287.0 3032.0 2012.0 \n",
"13 Peru 1267.0 1235.0 1449.0 1340.0 \n",
"6 Costa Rica 536.0 581.0 586.0 493.0 \n",
"15 Uruguay 431.0 558.0 475.0 451.0 \n",
"12 Paraguay 337.0 364.0 371.0 344.0 \n",
"8 Guatemala 212.0 258.0 289.0 274.0 \n",
"11 Panama 319.0 436.0 0.0 0.0 \n",
"9 Honduras 161.0 188.0 194.0 167.0 \n",
"1 Bolivia (Plurinational State of) 159.0 232.0 226.0 0.0 \n",
"7 El Salvador 147.0 146.0 149.0 147.0 \n",
"\n",
" Total \n",
"14 2379895.0 \n",
"3 145392.0 \n",
"2 98698.0 \n",
"10 62708.0 \n",
"0 14155.0 \n",
"4 12274.0 \n",
"5 9452.0 \n",
"13 5291.0 \n",
"6 2196.0 \n",
"15 1915.0 \n",
"12 1416.0 \n",
"8 1033.0 \n",
"11 755.0 \n",
"9 710.0 \n",
"1 617.0 \n",
"7 589.0 "
]
},
"execution_count": 6,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"\n",
"patent_applications = sparsed_df[['Office','Patent_applications_2020','Patent_applications_2021','Patent_applications_2022','Patent_applications_2023']]\n",
"\n",
"patent_applications['2020'] = patent_applications['Patent_applications_2020']\n",
"patent_applications['2021'] = patent_applications['Patent_applications_2021']\n",
"patent_applications['2022'] = patent_applications['Patent_applications_2022']\n",
"patent_applications['2023'] = patent_applications['Patent_applications_2023']\n",
"\n",
"patent_applications['Total'] = patent_applications['2020'] + patent_applications['2021'] + patent_applications['2022'] + patent_applications['2023']\n",
"\n",
"patent_applications.drop(columns=['Patent_applications_2020','Patent_applications_2021','Patent_applications_2022','Patent_applications_2023'], inplace=True)\n",
"\n",
"patent_applications.sort_values(by='Total', ascending=False)\n",
"\n",
"\n"
]
}
],
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