fcunhaneto

import pandas as pl
import matplotlib.pyplot as plt

"""
Incluindo annotates
"""
dataframe = pl.read_csv('annual-real-gnp-us-1909-to-1970.csv')

plt.figure(figsize=(8, 6))
plt.plot(dataframe['Year'], dataframe['GNP'])

fcunhaneto

import pandas as pl
import matplotlib.pyplot as plt

"""
Annotates dentro de um box
"""
dataframe = pl.read_csv('annual-real-gnp-us-1909-to-1970.csv')

plt.figure(figsize=(8, 6))
plt.plot(dataframe['Year'], dataframe['GNP'])

fcunhaneto

import pandas as pl
import matplotlib.pyplot as plt

"""
Incluindo texto no gráfico
"""
dataframe = pl.read_csv('annual-real-gnp-us-1909-to-1970.csv')

font_1 = {'family':'serif', 'color':'#FFFC19', 'fontsize':'large' }
font_2 = {'family':'fantasy', 'color':'yellow', 'size':'16'}

fcunhaneto

import pandas as pd
import matplotlib.pyplot as plt

"""
Lendo de um arquivo de texto
"""
with open('annual-real-gnp-us-1909-to-1970.txt, 'r') as f:
    # Usando a expressão regular para o separador indicando que eles são os
    # espaços em braco
    df = pd.read_table(f, sep='\s+')

fcunhaneto

import pandas as pl
import matplotlib.pyplot as plt

df = pl.read_csv('questionario.csv')

with open('questionario.txt', 'w') as f:
    df.to_string(f)

fcunhaneto

import numpy as np
import pandas as pd

def frequency_by_natural_order(dataframe, column):
    """
    Create a dataframe that gives the total by natural order, frequencies,
    accumulated total and frequency per item.
    Dataframe output example:

        tot  freq  tot_ac  freq_ac

fcunhaneto

import matplotlib.pyplot as plt
from pandasUteis.pandas_utils import frequency_by_natural_order, frequency_by_buckets

df = pd.read_csv('/home/francisco/Projects/Pycharm/'
                        'matplot-pandas-tutorial/files/questionario.csv')

"""
Criando um histograma para com os pesos dos alunos
"""
peso = df['Peso']

fcunhaneto

import pandas as pd
import matplotlib.pyplot as plt

df = pd.read_csv('/home/francisco/Projects/Pycharm/'
                        'matplot-pandas-tutorial/files/questionario.csv')

"""
Criando um histograma comparando os pesos masculino x feminino
"""
fem = df[df.Sexo == 'F']

fcunhaneto

import numpy as np
import pandas as pd

def frequency_by_buckets(dataframe, column, r, ini, end):
    """
    Creates a dataframe with cumulative values within a range, which are called
    buckets.
    Dataframe output example:

               tot  freq  tot_ac  freq_ac

fcunhaneto

import pandas as pd
import matplotlib.pyplot as plt

"""
Criando um boxplot para a coluna alturas, e para as alturas femininas e 
masculinas
"""
df = pd.read_csv('questionario.csv')

alt = df['Alt']