Python

Ciencia de Datos

Descripción

Programación en Python para el análisis y la ciencia de datos.

Objetivos

Por completar.

Contenidos / Sílabo

Python

1. Unidad 01

1.1 Python: Primeros pasos

2. Unidad 02

2.1 Python: Sintaxis
2.2 Python: Sentencias (Statements)

3. Unidad 03

3.1 Python: Salida con print()
3.2 Python: Salida de Números con print()

4. Unidad 04

4.1 Python: Comentarios

5. Unidad 05

5.1 Python: Variables
5.2 Python: Nombres de Variables
5.3 Python: Asignación Múltiple de Variables
5.4 Python: Salida de Variables
5.5 Python: Variables Globales
5.6 Python: Ejercicios de Variables

6. Unidad 06

6.1 Python: Tipos de Datos

7. Unidad 07

7.1 Python: Números

8. Unidad 08

8.1 Python: Casting (Conversión de Tipos)

9. Unidad 09

9.1 Python: Strings (Cadenas de Texto)
9.2 Python: Slicing de Strings
9.3 Python: Modificar Strings
9.4 string concatenation
9.5 format strings
9.6 escape characters
9.7 string methods
9.8 string excercises

10. Unidad 10

10.1 booleans

11. Unidad 11

11.1 operators
11.2 arithmetic operators
11.3 assignment operators
11.4 ternary operators
11.5 comparison operators
11.6 logical operators
11.7 identity operators
11.8 membership operators
11.9 bitwise operators
11.10 operator precedence

12. Unidad 12

12.1 lists
12.2 access list items
12.3 change list items
12.4 add list items
12.5 remove list items
12.6 loop lists
12.7 list comprehension
12.8 sort lists
12.9 copy lists
12.10 join lists
12.11 list methods
12.12 list exercises

13. Unidad 13

13.1 tuples
13.2 access tuple items
13.3 update tuples
13.4 unpack tuples
13.5 loop tuples
13.6 join tuples
13.7 tuple methods
13.8 tuple exercises

14. Unidad 14

14.1 sets
14.2 access set items
14.3 add set items
14.4 remove set items
14.5 loop sets
14.6 join sets
14.7 frozenset
14.8 set methods
14.9 set exercises

15. Unidad 15

15.1 dictionaries
15.2 access dictionary items
15.3 change dictionary items
15.4 add dictionary items
15.5 remove dictionary items
15.6 loop dictionaries
15.7 copy dictionaries
15.8 nested dictionaries
15.9 dictionary methods
15.10 dictionary exercises

16. Unidad 16

16.1 if
16.2 elif
16.3 else
16.4 shorthand if
16.5 logical operators
16.6 nested if
16.7 pass statement

17. Unidad 17

17.1 match

18. Unidad 18

18.1 while loops

19. Unidad 19

19.1 for loops

20. Unidad 20

20.1 functions
20.2 arguments
20.3 args kwargs
20.4 scope
20.5 decorators
20.6 lambda
20.7 recursion
20.8 generators

21. Unidad 21

21.1 range

22. Unidad 22

22.1 arrays

23. Unidad 23

23.1 iterators

24. Unidad 24

24.1 modules

25. Unidad 25

25.1 dates

26. Unidad 26

26.1 math

27. Unidad 27

27.1 json

28. Unidad 28

28.1 regex

29. Unidad 29

29.1 pip

30. Unidad 30

30.1 try except

31. Unidad 31

31.1 string formatting

32. Unidad 32

32.1 none

33. Unidad 33

33.1 user input

34. Unidad 34

34.1 virtualenv

35. Unidad 35

35.1 oop
35.2 classes objects
35.3 init method
35.4 self parameter
35.5 class properties
35.6 class methods
35.7 inheritance
35.8 polymorphism
35.9 encapsulation
35.10 inner classes

36. Unidad 36

36.1 file handling
36.2 read files
36.3 write create files
36.4 delete files

37. Unidad 37

37.1 numpy home
37.2 numpy intro
37.3 numpy getting started
37.4 numpy creating arrays
37.5 numpy array indexing
37.6 numpy array slicing
37.7 numpy data types
37.8 numpy copy vs view
37.9 numpy array shape
37.10 numpy array reshape
37.11 numpy array iterating
37.12 numpy array join
37.13 numpy array split
37.14 numpy array search
37.15 numpy array sort
37.16 numpy array filter
37.17 random intro
37.18 data distribution
37.19 random permutation
37.20 seaborn module
37.21 normal distribution
37.22 binomial distribution
37.23 poisson distribution
37.24 uniform distribution
37.25 logistic distribution
37.26 multinomial distribution
37.27 exponential distribution
37.28 chi square distribution
37.29 rayleigh distribution
37.30 pareto distribution
37.31 zipf distribution
37.32 ufunc intro
37.33 ufunc create function
37.34 ufunc simple arithmetic
37.35 ufunc rounding decimals
37.36 ufunc logs
37.37 ufunc summations
37.38 ufunc products
37.39 ufunc differences
37.40 ufunc finding lcm
37.41 ufunc finding gcd
37.42 ufunc trigonometric
37.43 ufunc hyperbolic
37.44 ufunc set operations
37.45 numpy certificate
37.46 numpy editor
37.47 numpy quiz
37.48 numpy exercises
37.49 numpy syllabus
37.50 numpy study plan

38. Unidad 38

38.1 pandas home
38.2 pandas intro
38.3 pandas getting started
38.4 pandas series
38.5 pandas dataframes
38.6 pandas read csv
38.7 pandas read json
38.8 pandas analyzing data
38.9 pandas cleaning data
38.10 pandas cleaning empty cells
38.11 pandas cleaning wrong format
38.12 pandas cleaning wrong data
38.13 pandas removing duplicates
38.14 pandas correlations
38.15 pandas plotting
38.16 pandas certificate
38.17 pandas editor
38.18 pandas quiz
38.19 pandas exercises
38.20 pandas syllabus
38.21 pandas study plan
38.22 pandas dataframes reference

39. Unidad 39

39.1 scipy home
39.2 scipy intro
39.3 scipy getting started
39.4 scipy constants
39.5 scipy optimizers
39.6 scipy sparse data
39.7 scipy graphs
39.8 scipy spatial data
39.9 scipy matlab arrays
39.10 scipy interpolation
39.11 scipy significance tests
39.12 scipy certificate
39.13 scipy editor
39.14 scipy quiz
39.15 scipy exercises
39.16 scipy syllabus
39.17 scipy study plan

40. Unidad 40

40.1 matplotlib intro
40.2 matplotlib get started
40.3 matplotlib pyplot
40.4 matplotlib plotting
40.5 matplotlib markers
40.6 matplotlib line
40.7 matplotlib labels
40.8 matplotlib grid
40.9 matplotlib subplot
40.10 matplotlib scatter
40.11 matplotlib bars
40.12 matplotlib histograms
40.13 matplotlib pie charts

41. Unidad 41

41.1 getting started
41.2 mean median mode
41.3 standard deviation
41.4 percentile
41.5 data distribution
41.6 normal data distribution
41.7 scatter plot
41.8 linear regression
41.9 polynomial regression
41.10 multiple regression
41.11 scale
41.12 train test
41.13 decision tree
41.14 confusion matrix
41.15 hierarchical clustering
41.16 logistic regression
41.17 grid search
41.18 categorical data
41.19 k-means
41.20 bootstrap aggregation
41.21 cross validation
41.22 auc roc curve
41.23 k-nearest neighbors

42. Unidad 42

42.1 python dsa
42.2 lists and arrays
42.3 stacks
42.4 queues
42.5 linked lists
42.6 hash tables
42.7 trees
42.8 binary trees
42.9 binary search trees
42.10 avl trees
42.11 graphs
42.12 linear search
42.13 binary search
42.14 bubble sort
42.15 selection sort
42.16 insertion sort
42.17 quick sort
42.18 counting sort
42.19 radix sort
42.20 merge sort

Bibliografía en Calibre (3):

ENAHO 2014. Cuestionario ENAHO.01A, módulo 300: educación — Instituto Nacional de Estadística e Informática (calibre 9993)
ENAHO 2014. Cuestionario ENAHO.01A, módulo 500: empleo e ingresos — Instituto Nacional de Estadística e Informática (calibre 9994)
ENAHO 2014. Diccionario de datos: condiciones de vida y pobreza — Instituto Nacional de Estadística e Informática (calibre 9995)

Fuente: 10 Class/docencia/cursos/python/curso.yml.

Bibliografía

Por completar.

Ediciones

Aún no hay ediciones publicadas. Próximamente.

Reutilización

CC BY-SA 4.0