Merging data using Python

Hello,

I am coding in Python, using Jupyter Notebook. I am also using Pandas and Beautiful Soup libraries for the tables.

I have already imported the relevant libraries at the top of my notebook.

I want to merge three data frames. I am doing research for a module I am taking.


1st data frame: Educational stage. https://en.wikipedia.org/wiki/Educational_stage

2nd data frame: Education in Canada. https://en.wikipedia.org/wiki/Education_in_Canada

3rd data frame: (r'E:\Umar Khan\UoL\Level 5 Modules\Programming with Data\Mid-Term\Umar-Khan-Research\global_education_data.csv')

# Set display options pd.set_option('display.max_rows', 9) pd.set_option('display.max_columns', 9) # Function to scrape tables from Wikipedia pages   def scrape_table(url):  res = requests.get(url)  soup = BeautifulSoup(res.content, 'html.parser')  table = soup.find_all('table')[0]    return pd.read_html(io.StringIO(str(table)))[0] # Scrape tables and load CSV   df1 = scrape_table('https://en.wikipedia.org/wiki/Educational_stage') df2 = scrape_table('https://en.wikipedia.org/wiki/Education_in_Canada') df3 = pd.read_csv(r'E:\Umar Khan\UoL\Level 5 Modules\Programming with Data\Mid-Term\Umar-Khan-Research\global_education_data.csv') # Concatenate dataframes df = pd.concat([df1, df2, df3], ignore_index=True) # Drop rows with missing data in specified columns   columns = ["Birth_Rate", "Gross_Primary_Education_Enrollment", "Gross_Tertiary_Education_Enrollment", "Unemployment_Rate"] df = df.dropna(subset=columns, thresh=1) # Filter out rows containing 0 or NaN df = df[(df != 0).all(axis=1)] # Identify columns with NaN nan_cols = df.columns[df.isna().any()] # Impute NaN with column means for col in nan_cols:  df[col] = df[col].fillna(df[col].mean())   # Check for remaining NaN   df.isna().any() # Display cleaned dataframe df.head()

As you can see from my attached image, I am getting NaN Values. I want data from the merge data there.

Thank you

I have solved my problem.

Well done What was the solution?