Global Emission Analysis Project

GLOBAL CLIMATE ANALYSIS/.gitattributes

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+# Auto detect text files and perform LF normalization
+* text=auto

GLOBAL CLIMATE ANALYSIS/.gitignore

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GLOBAL CLIMATE ANALYSIS/CLEAN AND PROCESSED/data perperation.py

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+import pandas as pd
+import numpy as np
+
+# Load the CSV data into a pandas DataFrame
+data = pd.read_csv('merge.csv')
+
+# Replace 0 with NaN
+data.replace(0, np.nan, inplace=True)
+
+# Display the first few rows of the DataFrame
+print(data.head())
+
+# Handle missing values, if any
+# For simplicity, we'll drop rows with missing values, but you could also fill them
+data = data.dropna()
+
+# Convert columns to appropriate data types if necessary
+data['latest year available_x'] = data['latest year available_x'].astype(int)
+
+# Save cleaned data for later use
+data.to_csv('cleaned_data.csv', index=False)
+
+
+

GLOBAL CLIMATE ANALYSIS/CLEAN AND PROCESSED/merge all.py

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+##Data Merging
+
+## Merge GHG Emissions Data
+
+##```python
+import pandas as pd
+# Load the data from CSV files
+ch4_data = pd.read_csv('CH4_N2O_Emissions.csv')
+co2_data = pd.read_csv('CO2_Emissions.csv')
+merged_ghg_emissions_data=pd.read_csv('merged_ghg_data.csv')
+NOx_data=pd.read_csv('NOx_Emissions.csv')
+Ods_data=pd.read_csv('ODS_Consumption.csv')
+SO2_data=pd.read_csv('SO2_emissions.csv')
+
+# Merge the datasets on the 'Country' column with outer join
+merged_data = ch4_data.merge(NOx_data, on='Country', how='outer')
+merged_data = merged_data.merge(co2_data, on='Country', how='outer')
+merged_data = merged_data.merge(merged_ghg_emissions_data, on='Country', how='outer')
+merged_data = merged_data.merge(Ods_data, on='Country', how='outer')
+merged_data = merged_data.merge(SO2_data, on='Country', how='outer')
+
+# Fill missing values with 0
+merged_data.fillna(0, inplace=True)
+
+# Save the merged data to a new CSV file
+merged_data.to_csv('merge.csv', index=False)
+
+# View the merged data
+print(merged_data.head())