# What are useful data structures with Python in your work as a data analyst/scientist?

Data Science in Python is ** less to do **with Data Structures and more with

**In-built Statistical Libraries**. But data structures like

**stacks, lists, dictionaries and tuples**are often used in Data Science. These are not the core but are the means to the

**more important Data Science and ML topics, which are**:

- Descriptive Statistics in Python
- Linear and Logistic Regression in Python
- Decision trees and Support vector machines in Python
- Neural Networks – RNN & CNN
- Deep Learning (Tensor flow and python)
- Spark and Python for Big data

So you need to focus on libraries more and need to have knowledge about the implementation of data structures. Let’s have a look on libraries available in python.

**Important libraries for Data Science and ML **in Python are:

- Basic Python Data Science libraries : Numpy, Scipy, Pandas , Matplotlib
- Machine learning libraries : Scikit-learn, Tensorflow, Theano