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Convert Array to DataFrame using Pandas in Python

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by vsasikalabe dot icon Updated: Feb 26, 2023

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Pandas is a Python library. It is used for working with collections of data. This function is used for analyzing, cleaning, exploring, and manipulating data. A Data Frame is similar to a 2D array. Remember that the input array must be 2D. Otherwise, you will get a ValueError. If you pass a raw array, the index and column names start at 0 by default. In Python, a lambda function is a function. It can take any number of arguments and execute an expression. We can create this expression by using the lambda keyword.  


Storing values in several dimensions are referred to as Multidimensional arrays. For example, an array in two dimensions is like a matrix, and an array in three dimensions can be a cube. In Python, using the NumPy library, multidimensional arrays are usually created. In this way, storing data can make it easier. And also to organize large amounts of data in a structure that is very easier to work with. A data frame is like an Excel sheet, i.e., a table of rows and columns. We can also create a Data Frame object from a dictionary of lists. The difference is that the key is the index, whereas the key is the column name in a Data Frame. 

Parameters: 

  • The first parameter is data, and it is the only one necessary. The array is required to turn into a data frame. 
  • Index: It returns the index information of the Data frame. RangeIndex is used by default if we don’t use this parameter. 
  • columns: These are labels for the columns in a data frame. If we don’t use this argument RangeIndex (0, 1, 2,…, n) is used by default. 


Here is an example of how to convert an Array to a Data frame using Pandas in Python: 

Preview of the output that you will get on running this code from your IDE.

Code

In this solution we used pandas library of python.

Array in DataFrame Panda Python

PythondotLines of Code : 15dotLicense : Strong Copyleft (CC BY-SA 4.0)

Dependent Libraries : 
import pandas as pd
data = {'c': [1, 2, 3, 4], 'date': [[1,2],[3],[0],[2,60,30,40]]}
df = pd.DataFrame(data)

df.loc[df['c']==4, 'date']
df.loc[df['c']==4, 'date'] = df.loc[df['c']==4, 'date'].apply(lambda i: sum(i))

[2, 60, 30, 40]

   c    date
0  1  [1, 2]
1  2     [3]
2  3     [0]
3  4     132

Instructions

Follow the steps carefully to get the output successfully:

  1. Install pandas on your IDE(Any of your favorite IDE)
  2. Create new python file in your IDE.(Pycharm Preferable)
  3. Copy the code using the "Copy" button above, and paste it in a Python file.
  4. Run the file to generate the output.


I hope you found this useful. I have added the link to dependent libraries, version information in the following sections.


I found this code snippet by searching for "Convert Array to DataFrame using Pandas in Python"in kandi. You can try any such use case

Environment Tested

I tested this solution in the following versions. Be mindful of changes when working with other versions.

  1. The solution is created in Python 3.11.1 Version
  2. The solution is tested on pandas 1.5.2 Version


Using this solution, we can Convert Array to DataFrame using Pandas in Python.This process also facilities an easy to use, hassle free method to create a hands-on working version of code in python.

Dependent Library

pandasby pandas-dev

Python doticonstar image 38689 doticonVersion:v2.0.2doticon
License: Permissive (BSD-3-Clause)

Flexible and powerful data analysis / manipulation library for Python, providing labeled data structures similar to R data.frame objects, statistical functions, and much more

Support
    Quality
      Security
        License
          Reuse

            pandasby pandas-dev

            Python doticon star image 38689 doticonVersion:v2.0.2doticon License: Permissive (BSD-3-Clause)

            Flexible and powerful data analysis / manipulation library for Python, providing labeled data structures similar to R data.frame objects, statistical functions, and much more
            Support
              Quality
                Security
                  License
                    Reuse

                      If you do not have pandas library that is required to run this code, you can install it by clicking on the above link.

                      You can search for any dependent library on kandi like pandas.

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