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#FURTHER EXPLORATORY DATA ANALYSIS

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1.1 EXPLORATORY DATA ANALYSIS OF THE ODS FILE IN PYTHON

import pandas as pd
!pip install ezodf
import ezodf

def read_ods_file():
    doc = ezodf.opendoc('final-greenhouse-gas-emissions-tables-2020.ods')
    sheet = doc.sheets[0]  # in order  to read the first sheet
    
    data = []
    for row in sheet.rows():
        row_data = [cell.value for cell in row]
        data.append(row_data)
    
    return data

# creating new dataframe for the ods file
ods_data = read_ods_file()

# Print the data
for row in ods_data:
    print(row)

1.2 EXPLORING FURTHER THE WORK SHEET CONTAINING THE RESEARCH DATA IN VIEW(METHANE EMMISSION)

def read_ods_file():
    doc = ezodf.opendoc('final-greenhouse-gas-emissions-tables-2020.ods')
    sheet = doc.sheets[5]  # Assuming you want to read the sixth sheet
    
    data = []
    for row in sheet.rows():
        row_data = [cell.value for cell in row]
        data.append(row_data)
    
    return data

# Replace 'your_file.ods' with the actual path to your .ods file
ods_data = read_ods_file()

# Print the data
for row in ods_data:
    print(row)
    
df = pd.DataFrame(ods_data[1:], columns=ods_data[6]) 
df.info()

1.30 CONVERTING THE ODS FILE TO CSV FILE

import ezodf
import csv

def convert_ods_to_csv(ods_file, csv_file):
    doc = ezodf.opendoc(ods_file)
    sheet = doc.sheets[5]  # SINCE WE want to read the SIXTH sheet CONTAINING METHANE EMISSIONS
    
    with open(csv_file, 'w', newline='', encoding='utf-8') as f:
        writer = csv.writer(f)
        for row in sheet.rows():
            row_data = [cell.value for cell in row]
            writer.writerow(row_data)

# Replace 'input_file.ods' and 'output_file.csv' with the actual file paths
convert_ods_to_csv('final-greenhouse-gas-emissions-tables-2020.ods', 'output_file.csv')

1.40 IGNORING UNNECESSARY ROWS BY SKIPPING TO THE MAIN COLUMN HEADERS

import pandas as pd
visuals1 = pd.read_csv("output_file.csv",skiprows=5) 
display (visuals1.head(10))
visuals1.info()
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