pandas_study.py

import pandas as pd

lista_survived = [0,1,1,1,0]

lista_pclass = [3,1,3,1,3]

lista_nomes = ['Mr. Owen Harris Braund',
               'Mrs. John Bradley (Florence Briggs Thayer Cumings)',
               'Miss. Laina Keikkinen',
               'Mrs. Jacques Heath (Lily May Peel) Futrelle',
               'Mr. William Henry Allen']

lista_sex = ['male','female','female','female','male']

lista_age = [22.0,38.0,26.0,35.0,35.0]

lista_spouses = [1,1,0,1,0]

lista_parents = [0,0,0,0,0]

lista_fare = [7.2500,71.2833,7.9250,53.10000,8.0500]

dados = list(zip(lista_survived,lista_pclass,lista_nomes,
                 lista_sex,lista_age, lista_spouses, lista_parents,
                 lista_fare))

titanic = pd.DataFrame(dados,columns=['Survived','Pclass','Name','Sex','Age',
                            'Siblings/Spouses Aboard',
                            'Parentes/Children Aboard','Fare'])


print(titanic.shape)
print(titanic.describe())
print(titanic.count())

series_titanic = pd.Series([10,20,30,40,50,60,70,80,90])

print(series_titanic.describe())

print(titanic.info())

print(titanic.Name)

url = 'https://en.wikipedia.org/wiki/Minnesota'

dfs = pd.read_html(url)

print(type(dfs))
print(len(dfs))

cobras = pd.DataFrame([[1,2],[4,5],[7,8]],
        index=['cobra','viper','sidewinder'],
        columns=('max_speed','shield'))

print(cobras.loc['viper'])

print(cobras.loc[['viper','sidewinder']])

filtro_homem = titanic['Sex'] == 'male'
titanic_homens = titanic.loc[filtro_homem]

print(titanic_homens)

titanic.drop_duplicates()