Best Data Analysis Tools to Buy in October 2025

Statistics: A Tool for Social Research and Data Analysis (MindTap Course List)



Data Analytics Essentials You Always Wanted To Know : A Practical Guide to Data Analysis Tools and Techniques, Big Data, and Real-World Application for Beginners (Self-Learning Management Series)



Data Analysis with Open Source Tools: A Hands-On Guide for Programmers and Data Scientists



Advanced Data Analytics with AWS: Explore Data Analysis Concepts in the Cloud to Gain Meaningful Insights and Build Robust Data Engineering Workflows Across Diverse Data Sources (English Edition)



Univariate, Bivariate, and Multivariate Statistics Using R: Quantitative Tools for Data Analysis and Data Science



Spatial Health Inequalities: Adapting GIS Tools and Data Analysis



Python for Excel: A Modern Environment for Automation and Data Analysis


To read a column in pandas as a column of lists, you can use the apply
method along with the lambda
function. By applying a lambda function to each element in the column, you can convert the values into lists. This way, you can read a column in pandas as a column of lists.
How to read in pandas column as column of lists in Python?
You can read a column in pandas as a column of lists by using the read_csv()
function and specifying the converters
parameter to convert the column into a list. Here's an example:
import pandas as pd
Create a sample dataframe
data = { 'column_with_lists': ['[1, 2, 3]', '[4, 5, 6]', '[7, 8, 9]'] } df = pd.DataFrame(data)
Define a function to convert string representation of lists into lists
def convert_to_list(lst_str): return eval(lst_str)
Read the column as a column of lists
df['column_with_lists'] = df['column_with_lists'].apply(convert_to_list)
Print the dataframe
print(df)
In this example, we have a column called column_with_lists
with string representations of lists. We define a function convert_to_list
that converts each string representation into a list using the eval()
function. We then apply this function to the column using the apply()
method, which converts the column into a column of lists.
How to concatenate pandas columns into a single column of lists?
You can concatenate multiple columns in a DataFrame into a single column of lists by using the apply
method along with a lambda function. Here's an example:
import pandas as pd
Sample DataFrame
df = pd.DataFrame({'A': [1, 2, 3], 'B': [4, 5, 6], 'C': [7, 8, 9]})
Concatenate columns A, B, and C into a single column of lists
df['combined'] = df.apply(lambda row: [row['A'], row['B'], row['C']], axis=1)
print(df)
This will create a new column called 'combined' in the DataFrame df
which contains lists of values from columns A, B, and C for each row.
Output:
A B C combined 0 1 4 7 [1, 4, 7] 1 2 5 8 [2, 5, 8] 2 3 6 9 [3, 6, 9]
You can adjust the lambda function as needed to concatenate specific columns or customize the list output.
What is the maximum number of lists that can be stored in a pandas column?
There is no specific limit to the number of lists that can be stored in a pandas column. The maximum number of lists that can be stored will depend on the available memory of the system. However, it is generally recommended to avoid storing large numbers of lists in a single column as it can impact performance and memory usage.