Commit: 122e257ab677afde702863fd5c1bf7e8b20206e2 - myprojects-hg-reborn (hg)

Commit MetaInfo

• Revision: 122e257ab677afde702863fd5c1bf7e8b20206e2 (tree)
• Zeit: 2024-09-04 22:41:45
• Autor: Lorenzo Isella <lorenzo.isella@gmai...>
• Commiter: Lorenzo Isella

Log Message

ChatGPT translation of my R code to calculate the kpi by DG grow.

Ändern Zusammenfassung

• add: Python-codes/create_kpi_grow.py

Diff

diff -r a99e1e0476a0 -r 122e257ab677 Python-codes/create_kpi_grow.py
--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/Python-codes/create_kpi_grow.py	Wed Sep 04 15:41:45 2024 +0200
@@ -0,0 +1,46 @@
+import pandas as pd
+import matplotlib.pyplot as plt
+
+# Define the Herfindahl-Hirschman Index (HHI) function
+def hhi_index(x):
+    y = x / x.sum()
+    res = (y**2).sum()
+    return res
+
+# Load the dataset
+df = pd.read_csv("../../input/scb_data_for_figures-19-02-2024.tar.gz", compression='gzip')
+
+# Clean column names (convert to lowercase and replace spaces with underscores)
+df.columns = df.columns.str.lower().str.replace(' ', '_')
+
+# Group by 'expenditure_year' and 'member_state_2_letter_codes' and summarize
+df_hhi = (df.groupby(['expenditure_year', 'member_state_2_letter_codes'])
+            .agg(exp_eur_bn=('aid_element_eur_bn', 'sum'),
+                 ms_gdp_eur_bn=('gdp_eur_bn', 'first'))
+            .reset_index())
+
+# Group by 'expenditure_year', calculate shares, and then calculate HHI
+df_hhi = (df_hhi.groupby('expenditure_year')
+            .apply(lambda x: pd.Series({
+                'hhi_aid': hhi_index(x['exp_eur_bn'] / x['exp_eur_bn'].sum()) * 1e4,
+                'hhi_gdp': hhi_index(x['ms_gdp_eur_bn'] / x['ms_gdp_eur_bn'].sum()) * 1e4
+            }))
+            .reset_index())
+
+
+# Plot hhi_aid against expenditure_year (First Plot)
+plt.figure(figsize=(10, 6))
+## plt.plot(df_hhi['hhi_aid'], df_hhi['expenditure_year'], 'g-', label='HHI Aid vs Year (reversed)')  # Green line for reverse plot
+plt.plot(df_hhi['expenditure_year'], df_hhi['hhi_aid'], 'b-', label='Year vs HHI Aid')  # Blue line for standard plot
+
+plt.plot(df_hhi['expenditure_year'], df_hhi['hhi_gdp'], 'b-', label='Year vs HHIGDP')  # Blue line for standard plot
+
+
+# Add labels and title
+plt.xlabel('Expenditure Year')
+plt.ylabel('HHI Aid')
+plt.title('HHI Aid Over Time')
+
+# Display the legend and plot
+plt.legend()
+plt.show()