This public repository contains the training materials, tutorials, code, and assignments for the Intensive Python Course at PUCP. The syllabus and structure of this course was created by Carla Solis. Please, check her Python Course for further details.
| Course name | Python Fundamentals for CCSS and Public Management |
| Number of Hours of Theory | 18 hours |
| Professor | Alexander Quispe Rojas |
| PUCP email | [email protected] |
| Teaching Assistant | Anzony Quispe Rojas |
| [email protected] |
The course will address the essential elements to develop programming skills with Python. In particular, the goal is to incorporate Python as a toolbox for quantitative research in the social sciences. This introduction will focus on data management and lay the foundation for training students in data science. Basic programming concepts such as data structures, defining functions, and working with essential specialized libraries for working with data, especially Numpy and Pandas, will be taught.
This course is intended for social science students and professionals with no prior experience with programming languages or who have just started using statistical programs such as Stata and have found it attractive to interact with data through code. Ultimately, this course seeks to prepare students for the job market by providing highly demanded skills, which will prepare them for a first job or internship that involves data science.
The course aims to familiarize and develop with Python so that students can autonomously use data science tools in their research and future job positions. At the end of the course, students will be able to:
- Interact with Python through Jupyter notebooks and master Markdown writing.
- Write code that solves daily data analysis tasks.
- Github
- Listas, Diccionarios, Numpy
- Pandas
- If condition, loop
- Funciones and Clases I
- Clases 2
Classes will be given synchronously using Zoom. In exploring the use of Python for data analysis, the use of databases for the social sciences will be emphasized.
The evaluation will consist of 5 projects. The minimum grade will be deleted.
| N° | Project | Weighting on Final Grade | Date | due |
|---|---|---|---|---|
| 1 | Assignment 1 | 20% | 12/17/2022 | 01/06/2023 |
| 2 | Assignment 2 | 20% | 01/07/2023 | 01/13/2023 |
| 3 | Assignment 3 | 20% | 01/14/2023 | 01/20/2023 |
| 4 | Assignment 4 | 20% | 01/21/2023 | 01/27/2023 |
| 5 | Assignment 5 | 20% | 01/28/2023 | 02/03/2023 |
This course will not have a mandatory bibliography. Python is a widely supported language with extensive documentation and a very large community that supports each other through Stack Overflow and other forums. For this reason, the class notes will be the primary reference material of the course.
| Week | Date | Day | Schedule | Topic | Subtopic |
|---|---|---|---|---|---|
| 1 | 12/10/2022 | Saturday | 14:00-17:00 | Github |
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| 2 | 12/17/2022 | Saturday | 14:00-17:00 | Basic Objects |
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| 3 | 01/07/2023 | Saturday | 14:00-17:00 | Pandas |
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| 4 | 01/14/2023 | Saturday | 14:00-17:00 | If and Loops |
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| 5 | 01/21/2023 | Saturday | 14:00-17:00 | Functions and Classes I |
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| 6 | 01/28/2023 | Saturday | 14:00-17:00 | Classes II |
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Matthes, E. (2016). Python crash course: A hands – on, project-based introduction to programming (2nd ed.). No Starch Press. ISBN: 9781593279288
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McKinney, W. (2013). Python for Data Analysis: Data Wrangling with Pandas, NumPy, and IPython. O'Reilly Media. ISBN: 9789351100065
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VanderPlas, J. (2016). Python Data Science Handbook. O'Reilly Media. ISBN: 9781491912058
| Grupo 1 | Grupo 2 | Grupo 3 | Grupo 4 | Grupo 5 |
|---|---|---|---|---|
| CORNEJO SANCHEZ, CHRISTIAN SANTOS | TINTAYA ORIHUELA, MEIR ALVARO | LUZON CUEVA, BIANCA MARIETTE | MEZA HINOJO, GUSTAVO | TORRES ANICAMA, JANE CAMILA |
| ORELLANA QUISPE, CRISTIAN NASSER | CHAVEZ MARTINEZ, JOSELIN ALEXANDRA | SUAÑA ZEGARRA, ADRIAN ANDRE | LOZADA MURILLO, PERSEO MARCELO | LOPEZ ESTRADA, MARIA ELISA |
| MORALES CHOQUEHUANCA, ANGELICA KARINA | FIGUEROA MURO, LEONEL ARTURO | SOTO POMACHAGUA, DORKAS YOMIRA JHERMY | ZAMBRANO JIMENEZ, MIGUEL ALONZO | BOYCO ORAMS, ALEJANDRO |
| GUIMARAY RIBEYRO, JOSE ROBERTO | GOMEZ CRIBILLERO, JOSE FELIPE | FIORENTINO MARTINEZ, LADY ALY | JACOBS LUQUE, NICOLAS | DIAZ BERROSPI, KARLINE ROSMELI |
| CAMACHO GAVIDIA, ABEL FERNANDO | PALOMINO SEGUÍN, AFRANIA | LAMA MAVILA, HECTOR ANDRE | VIDAL VIDAL, ROCIO GABRIELA | RIEGA ESCALANTE, STEPHY ROSARIO |
| HUANCA MARTINEZ, JORGE ALBERTO | FLORES CADILLO, ALEXIS |
| Grupo 6 | Grupo 7 | Grupo 8 | Grupo 9 | Grupo 10 |
|---|---|---|---|---|
| LEVANO TORRES, VALERIA CECILIA | AGUILAR GARCIA, ERICK JOSUE | HUANCAYA IDONE, CESAR DANTE | HINOJOSA CAHUANA, PERCY ALBERTH | SOTO PACHERRES, RODRIGO FRANCO |
| ESQUIVES BRAVO, SEBASTIAN RENATO | CALDAS VELASQUEZ, JOSUE DANIEL | CALVO PORTOCARRERO, GABRIELA ISABEL | ANGLAS GARCÍA, KEVIN ARTURO | INGARUCA RIVERA, GRETTEL ALEXANDRA |
| PEREZ GONZALES, JUAN CARLOS | SALAS NUÑEZ BORJA, FABIO MANUEL | IBAÑEZ ABANTO, ANGEL MAURICIO | ALDAVE ACOSTA, CESAR ERNESTO | ROJAS HUAMAN, ROSA ANGELA |
| OTERO MAGUIÑA, MARIANA | PIZARRO VILLANES, FERNANDA NICOLLE | MELÉNDEZ APONTE, JUAN DIEGO | NÚÑEZ HUAMÁN, CÉSAR AGUSTO | NEYRA SALAS, DANTE OMAR |
| CLAVO CAMPOS, ANDREA BRIZETH | QUILLATUPA MORALES, ANGELA ADELINA | CRISTIAN SERRANO, ARONE | OBREGON HUAMAN, DIANA EDITH | HUERTA ESPINOZA, YAJAIRA ALEXANDRA |