import pandas as pd
import numpy as np

############# Creacion y despliege de una serie

s = pd.Series([-2, 0, 3, 6])
print(s)

############# tipo de datos, indices y valores de una serie

ventas = pd.Series([15, 12, 21], index =["Enero", "Febrero", "Marzo"])
print(ventas)
ventas[0]
ventas["Enero"]
ventas.dtype
ventas.index
ventas.values

############# Creacion y despliege de una dataframe

ventas2 = pd.DataFrame({
    "Entradas": [41, 32, 56, 18],
    "Salidas": [17, 54, 6, 78],
    "Valoraciones": [66, 54, 49, 66],
    "Limite": ["No", "Si", "No", "No"],
    "Cambio": [1.43, 1.16, -0.67, 0.77],
}, index =["Enero", "Febrero", "Marzo", "Abril"])

print(ventas2)

ventas2.index.name = "Meses" # renombre del conjunto de indices
ventas2.columns.name = "Métricas" #renombre del conjunto de columnas

########### Metodo combnando series en un dataframe

entradas = pd.Series([11, 18, 12, 16, 9, 16, 22, 28, 31, 29, 30, 12],
    index = ["ene", "feb", "mar", "abr", "may", "jun", "jul", "ago", "sep", "oct", "nov", "dic"])
print(entradas)

salidas = pd.Series([9, 26, 18, 15, 6, 22, 19, 25, 34, 22, 21, 14],
    index = ["ene", "feb", "mar", "abr", "may", "jun", "jul", "ago", "sep", "oct", "nov", "dic"])
print(salidas)

almacen = pd.DataFrame({"entradas": entradas, "salidas": salidas})
almacen["neto"] = almacen.entradas - almacen.salidas

print(almacen)

print(almacen.head()) #las primaras 5 filas

print(almacen.tail()) #las ultimas 5 filas

almacen.describe()

################## Metodo value_counts

s = pd.Series([3, 1, 2, 1, 1, 4, 1, 2, np.nan])

s.value_counts()

s.value_counts(dropna = False) #incluir valores nulos

s.value_counts(bins = 2)

############################### carga de un dataframe desde un diccionario

students = [{
    "name":"Jorge",
    "surname":"Perez",
    "age":24,
    "weight":50,
    "height": 170
},{
    "name":"Pepe",
    "surname":"Garcia",
    "age":27,
    "weight":60,
    "height": 175
},
{
    "name":"Aria",
    "surname":"Jimenez",
    "age":26,
    "weight":70,
    "height": 180
},
{
    "name":"Maria",
    "surname":"Ruz",
    "age":25,
    "weight":75,
    "height": 181
},
{
    "name":"Luisa",
    "surname":"Perez",
    "age":24,
    "weight":50,
    "height": 170
},
{
    "name":"Luisa",
    "surname":"Perez",
    "age":24,
    "weight":50,
    "height": 170
}]

ds = pd.DataFrame(students)
print ds