sinhrks

import string

from pandas import DataFrame

import numpy as np
from numpy.random import randn, rand

import pandas.tools.plotting as plotting

from matplotlib.pylab import close

sinhrks

from pandas import DataFrame, Series
from numpy.random import randn, rand

df1 = DataFrame(randn(6, 3), index=range(6),
               columns=['a', 'b', 'c'])

df2 = DataFrame(randn(6, 3), index=range(6),
               columns=['d', 'e', 'f'])

df3 = DataFrame(randn(6, 3), index=range(6),

sinhrks

import string

from pandas import DataFrame, Series
from numpy.random import randn
import matplotlib.pyplot as plt

df = DataFrame(randn(7, 4),
               index=list(string.ascii_letters[:7]),
               columns=['x', 'y', 'z', 'four'])
series = Series(randn(7), index=range(7))

sinhrks

# -*- coding: utf-8 -*-
import string
 
from pandas import DataFrame, Series
import datetime
import numpy as np
from numpy.random import randn, rand
 
import pandas.tools.plotting as plotting
from pandas.compat import u, string_types

sinhrks

import pandas as pd
import numpy as np
import pandas.util.testing as tm
import matplotlib.pyplot as plt

import pandas as pd
import numpy as np

series = pd.Series(3 * np.random.rand(4), index=['a', 'b', 'c', 'd'], name='series')

sinhrks

set.seed(1)

# 観測系列のサンプルサイズ
n <- 120

# 真の値
actual <- rep(5, out.length = n)

# 観測される値 (誤差は標準偏差2の正規分布とする)
observed <- actual + rnorm(n, mean = 0, sd = 2)

sinhrks

set.seed(1)

# 観測系列のサンプルサイズ
n <- 200

# 真の値が時間変化する
actual <- 3.0 + cumsum(rnorm(n, sd = 0.2))

# 観測される値 (誤差は標準偏差2の正規分布とする)
observed <- actual + rnorm(n, mean = 0, sd = 2)

sinhrks

set.seed(1)

# 観測系列のサンプルサイズ
n <- 100

# 真の値
x <- c(rep(0, n / 4), seq(0, 10, length.out = n / 4),
       rep(10, n / 4), seq(10, 0, length.out = n / 4))
y <- c(seq(0, 10, length.out = n / 4), rep(10, n / 4),
       seq(10, 0, length.out = n / 4), rep(0, n / 4))

sinhrks

set.seed(1)

# 観測系列のサンプルサイズ
n <- 30

# 加速度
a <-rep(0.3, n)

v <- cumsum(0.5 * a)
x <- cumsum(v)

sinhrks

# -*- coding: utf-8 -*-
import numpy as np
import pandas as pd

import matplotlib.pyplot as plt
import matplotlib.animation as animation

# rpy2 経由で R から iris をロード
# import pandas.rpy.common as com
# iris = com.load_data('iris')