Create a Series from a List, Numpy Array, and Dictionary in Pandas

Pandas is an open-source Python Library providing high-performance data manipulation and analysis tool using its powerful data structures. The name Pandas is derived from the word Panel Data – an Econometrics from Multidimensional data.

Series is a one-dimensional labelled array capable of holding data of any type i.e. integer, string, float, python objects, etc). The axis labels are collectively called index.

To create a series, at first install the pandas library. We use pip to install any library in Python −

pip install pandas

Create a Pandas Series from a List

Example

We will create a series from a List using the series(). The list will be set as a parameter −

import pandas as pd

# Create a List
myList = [5, 10, 15, 20, 25, 30]

# Create a Pandas series using the series() method
res = pd.Series(myList)
print("Series = \n",res)

Output

Series = 
0     5
1    10
2    15
3    20
4    25
5    30
dtype: int64

Create a Pandas Series from a Numpy Array

To create a series from a numpy array, use the numpy library −

import numpy as np

Example

Let us see an example −

import pandas as pd
import numpy as np

# Create an array using numpy.array()
arr = np.array([5, 10, 15, 20, 25, 30])

# Create a Pandas series using the Numpy array
res = pd.Series(arr)
print("Series = \n",res)

Output

Series = 
0     5
1    10
2    15
3    20
4    25
5    30
dtype: int64

Create a Pandas Series from a Dictionary

Example

In this example, we will create a series from Dictionary with key-value pairs −

import pandas as pd
import numpy as np

# Create a Dictionary with Keys and Values
d = {
   "A":"demo",
   "B": 40,
   "C": 25,
   "D": "Yes"
}

# Create a Pandas series using Dictionary
res = pd.Series(d)
print("Series = \n",res)

Output

Series = 
A       demo
B       40
C       25
D       Yes
dtype:  object