Explain how a dataframe structure can be created using list of dictionary values in Python?

Dataframe is a two dimensional data structure, where data is stored in a tabular format, in the form of rows and columns.

It can be visualized as an SQL data table or an excel sheet representation.

It can be created using the following constructor −

pd.Dataframe(data, index, columns, dtype, copy)

The ‘data’, ‘index’, ‘columns’, ‘dtype’ and ‘copy’ are not compulsory values.

A list of dictionaries can be passed as input to the dataframe. The keys of dictionary are taken as column names by default. Let us see an example −

Example

 Live Demo

import pandas as pd
my_data = [{'ab' : 34}, {'mn' : 56},{ 'gh' : 78}, {'wq' : 90},{'az' : 123},{'kl' : 45}]
my_df = pd.DataFrame(my_data)
print("The dataframe created from list of dictionary : ")
print(my_df)

Output

The dataframe created from list of dictionary :
   ab    az    gh   kl   mn    wq
0  34.0  NaN  NaN   NaN  NaN   NaN
1  NaN  NaN   NaN   NaN  56.0  NaN
2  NaN  NaN   78.0  NaN  NaN   NaN
3  NaN  NaN   NaN   NaN  NaN   90.0
4  NaN  123.0 NaN   NaN  NaN   NaN
5  NaN  NaN   NaN  45.0  NaN   NaN

Explanation

• The required libraries are imported, and given alias names for ease of use.

• A list of dictionary values is created, wherein a key-value pair is present in one dictionary.

• In this way, multiple dictionaries are created and stored in a list.

• This list of dictionary is later passed as a parameter to the ‘Dataframe’ function present in the ‘pandas’ library

• The dataframe is created by passing the list of dictionary values as parameters to it.

• The dataframe is printed on the console.

Note − The word ‘NaN’ refers to ‘Not a Number’, which means that specific [row,col] value doesn’t have any valid entry.