Write a Python code to combine two given series and convert it to a dataframe

When working with Pandas Series, you often need to combine them into a single DataFrame for analysis. Python provides several methods to achieve this: direct DataFrame creation, concatenation, and joining.

Method 1: Using DataFrame Constructor

Create a DataFrame from the first series, then add the second series as a new column ?

import pandas as pd

series1 = pd.Series([1, 2, 3, 4, 5], name='Id')
series2 = pd.Series([12, 13, 12, 14, 15], name='Age')

df = pd.DataFrame(series1)
df['Age'] = series2
print(df)

   Id  Age
0   1   12
1   2   13
2   3   12
3   4   14
4   5   15

Method 2: Using pd.concat()

Concatenate both series horizontally using axis=1 parameter ?

import pandas as pd

series1 = pd.Series([1, 2, 3, 4, 5], name='Id')
series2 = pd.Series([12, 13, 12, 14, 15], name='Age')

df = pd.concat([series1, series2], axis=1)
print(df)

   Id  Age
0   1   12
1   2   13
2   3   12
3   4   14
4   5   15

Method 3: Using join()

Create a DataFrame from the first series and join the second series ?

import pandas as pd

series1 = pd.Series([1, 2, 3, 4, 5], name='Id')
series2 = pd.Series([12, 13, 12, 14, 15], name='Age')

df = pd.DataFrame(series1)
df = df.join(series2)
print(df)

   Id  Age
0   1   12
1   2   13
2   3   12
3   4   14
4   5   15

Comparison

Conclusion

Use pd.concat() for combining multiple series efficiently. Use DataFrame constructor for simple two-series combinations. The join() method works well when adding series to existing DataFrames.