Pandas
Prof. Dr. Nicolas Rohleder, Prof. Dr. Björn Eskofier, Veronika Ringgold, Luca Abel, Robert Richer · 10 concepts · 10 questions
Concept 1 / 10
What pandas Is and Why It Matters
pandas is a fast, flexible, open-source Python library for data analysis and manipulation. It is the workhorse of tabular data work in the sciences — loading questionnaires, sensor exports, and clinical tables into memory and reshaping them for analysis.
pandas is built on top of NumPy, so many functions behave identically or very similarly (np.mean, axis=, boolean masks, etc.). The two central data structures are:
| Structure | Dimensions | Analogy |
|---|---|---|
pd.Series | 1-D | A single labelled column |
pd.DataFrame | 2-D | A whole table (rows × columns) |
The conventional import alias is pd:
import pandas as pd
import numpy as npUnlike a raw NumPy array, a DataFrame attaches labels to every row and column, which makes selecting, aligning, and grouping data far more expressive.