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

Assume, you have two series and the result for combining two series into dataframe as,

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

To solve this, we can have three different approaches.

Solution 1

• Define two series as series1 and series2

• Assign first series into dataframe. Store it as df

df = pd.DataFrame(series1)

• Create a column df[‘Age’] in dataframe and assign second series inside to df.

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

Example

Let’s check the following code to get a better understanding −

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'] = pd.DataFrame(series2)
print(df)

Output

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

Solution 2

• Define a two series

• Apply pandas concat function inside two series and set axis as 1. It is defined below,

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

Example

Let’s check the following code to get a better understanding −

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)

Output

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

Solution 3

• Define a two series

• Assign first series into dataframe. Store it as df

df = pd.DataFrame(series1)

• Apply pandas join function inside series2. It is defined below,

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

Example

Let’s check the following code to get a better understanding −

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)

Output

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