Create a Pandas DataFrame from Lists

Python is a great language for data analysis, primarily because of the fantastic ecosystem of data-centric Python packages. Pandas is one of those packages, making importing and analyzing data much easier. Creating a Pandas Dataframe can be achieved in multiple ways. Let’s see how we can create a Pandas DataFrame from Lists.

Creating Pandas DataFrames from Lists

Converting lists to DataFrames is crucial in data analysis, enabling you to perform sophisticated data manipulations and analyses with ease.

Here we will discuss different ways to create a Pandas Dataframe from the lists:

• Create Dataframe from List using Constructer
• Create DataFrame from List using Dictionary
• Create DataFrame from list using zip()
• Create DataFrame from list by changing data type
• Create DataFrame from list using multi-dimensional list
• Create DataFrame from List with index and column names

Create Dataframe from List using Constructer

To convert a list to a Pandas DataFrame, you can use the pd.DataFrame() constructor. This function takes a list as input and creates a DataFrame with the same number of rows and columns as the input list.

Python3

# import pandas as pd
import pandas as pd

# list of strings
lst = ['Geeks', 'For', 'Geeks', 'is',
            'portal', 'for', 'Geeks']

# Calling DataFrame constructor on list
df = pd.DataFrame(lst)
print(df)

Output:

 0
0   Geeks
1     For
2   Geeks
3      is
4  portal
5     for
6   Geeks

Create DataFrame from List using Dictionary

To use lists in a dictionary to create a Pandas DataFrame, we Create a dictionary of lists and then Pass the dictionary to the pd.DataFrame() constructor. Optionally, we can specify the column names for the DataFrame by passing a list of strings to the columns parameter of the pd.DataFrame() constructor.

Python3

# importing pandas as pd
import pandas as pd

# list of name, degree, score
nme = ["aparna", "pankaj", "sudhir", "Geeku"]
deg = ["MBA", "BCA", "M.Tech", "MBA"]
scr = [90, 40, 80, 98]

# dictionary of lists
dict = {'name': nme, 'degree': deg, 'score': scr}

df = pd.DataFrame(dict)

print(df)

Output:

 name  degree  score
0  aparna     MBA     90
1  pankaj     BCA     40
2  sudhir  M.Tech     80
3   Geeku     MBA     98

Create DataFrame from List using zip()

To create a Pandas DataFrame from lists using zip(). We can also use the zip() function to zip together multiple lists to create a DataFrame with more columns.

Python3

# import pandas as pd
import pandas as pd

# list of strings
lst = ['Geeks', 'For', 'Geeks', 'is', 'portal', 'for', 'Geeks']

# list of int
lst2 = [11, 22, 33, 44, 55, 66, 77]

# Calling DataFrame constructor after zipping
# both lists, with columns specified
df = pd.DataFrame(list(zip(lst, lst2)),
               columns =['Name', 'val'])
print(df)

Output:

Name  val
0   Geeks   11
1     For   22
2   Geeks   33
3      is   44
4  portal   55
5     for   66
6   Geeks   77

Create DataFrame from List by changing data type

To create a Pandas DataFrame using a multi-dimensional list with column names and dtypes specified. By specifying dtypes, we can ensure that the DataFrame is created with the correct data types.

Python3

# import pandas as pd
import pandas as pd

# List1
lst = [['tom', 'reacher', 25], ['krish', 'pete', 30],
       ['nick', 'wilson', 26], ['juli', 'williams', 22]]

df = pd.DataFrame(lst, columns =['FName', 'LName', 'Age'], dtype = float)
print(df)

Output:

FName     LName   Age
0    tom   reacher  25.0
1  krish      pete  30.0
2   nick    wilson  26.0
3   juli  williams  22.0

Create DataFrame from List using multi-dimensional list

To create a DataFrame using a multi-dimensional list, you can use the pd.DataFrame() constructor. The pd.DataFrame() constructor takes a list of lists as input and creates a DataFrame with the same number of rows and columns as the input list.

Python3

# import pandas as pd
import pandas as pd

# List1
lst = [['tom', 25], ['krish', 30],
       ['nick', 26], ['juli', 22]]

df = pd.DataFrame(lst, columns =['Name', 'Age'])
print(df)

Output:

Name  Age
0    tom   25
1  krish   30
2   nick   26
3   juli   22

Create DataFrame from List with index and column names

To create a DataFrame using a list with index and column names, you can use the pd.DataFrame() constructor with the index and columns parameters.

Python3

# import pandas as pd
import pandas as pd

# list of strings
lst = ['Geeks', 'For', 'Geeks', 'is', 'portal', 'for', 'Geeks']

# Calling DataFrame constructor on list
# with indices and columns specified
df = pd.DataFrame(lst, index =['a', 'b', 'c', 'd', 'e', 'f', 'g'],
                                              columns =['Names'])
print(df)

Output:

Names
a   Geeks
b     For
c   Geeks
d      is
e  portal
f     for
g   Geeks