# Python & Pandas - Fundamentals (Data Analytics)

> DataFrames, Series, indexing (loc, iloc), boolean filtering, data types, read_csv, describe, info, head/tail, shape, columns

- 20 interview questions
- Junior
- [Interview Questions: Data Analytics](https://sharpskill.dev/en/technologies/data-analytics/interview-questions.md)

## 1. What is the main Pandas data structure for storing tabular data?

**Answer**

The DataFrame is the core Pandas data structure. It represents a two-dimensional table with rows and columns, similar to a spreadsheet or SQL table. Each column is a Series, and each row has an index. The DataFrame enables efficient manipulation of structured data through its many built-in methods.

## 2. What is a Series in Pandas?

**Answer**

A Series is a one-dimensional array with an index. It represents a single column of data in a DataFrame. Each element has a label (index) enabling fast access by name or position. A Series can hold only one data type (int, float, string, etc.), which distinguishes it from a plain Python list.

## 3. Which Pandas function reads a CSV file and loads it into a DataFrame?

**Answer**

The pd.read_csv() function reads a CSV file and returns a DataFrame. It accepts many parameters: sep for the delimiter, header for the header row, encoding for file encoding, dtype to force column types, and na_values to define missing values. It is the most common method to import data into Pandas.

## 17 more questions available

- What does the df.shape attribute return on a DataFrame?
- Which method displays the first 5 rows of a DataFrame?

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