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## seaborn_plot_without_set.ipynb

      
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                / seaborn_plot_without_set.ipynb
            
            
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              April 10, 2018 03:02
            
              
                set()しないとこうなる
              
          
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## seaborn_plot_with_set.ipynb

      
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              April 10, 2018 03:03
            
              
                seabornをimportしたらset()する
              
          
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## legend_test.ipynb

      
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                / legend_test.ipynb
            
            
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              January 9, 2018 05:53
            
              
                seabornを使ったプロットの凡例を見やすく
              
          
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## pandas_to_sklean.ipynb

      
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              December 27, 2017 02:16
            
              
                pandasからnparrayに直す手習い
              
          
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## pickle_test.ipynb

      
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                / pickle_test.ipynb
            
            
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              December 26, 2017 05:59
            
              
                Pickleとjoblibのテスト
              
          
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## matplotloib_sample.ipynb

      
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              September 23, 2016 01:47
            
              
                matplotlib_sample
              
          
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## py_kinji.py
import pandas as pd
from matplotlib import pyplot as plt
import seaborn as sns
import numpy as np
from scipy import optimize as opt

kion = pd.read_csv("kion_20160501.csv")
kion.head()

Px = np.arange(0, len(kion), 1)

## kion_kinji.r
library(ggplot2)

kion = read.csv("kion_20160501.csv", header = T, colClasses = c("POSIXct", "numeric"))
head(kion)
summary(kion)

g = ggplot(kion, aes(1:nrow(kion), temp)) + geom_line(colour="blue") + labs(title="2016/05/01")
plot(g)

x = 1:nrow(kion)

## ggpairs_color.r
library(ggplot2)
library(GGally)
ggpairs(iris, aes_string(colour="Species", alpha=0.5))


## ggpairs_bw.r
library(GGally)
ggpairs(iris, colour="Species", alpha=0.5)
	import pandas as pd
	from matplotlib import pyplot as plt
	import seaborn as sns
	import numpy as np
	from scipy import optimize as opt

	kion = pd.read_csv("kion_20160501.csv")
	kion.head()

	Px = np.arange(0, len(kion), 1)
	library(ggplot2)

	kion = read.csv("kion_20160501.csv", header = T, colClasses = c("POSIXct", "numeric"))
	head(kion)
	summary(kion)

	g = ggplot(kion, aes(1:nrow(kion), temp)) + geom_line(colour="blue") + labs(title="2016/05/01")
	plot(g)

	x = 1:nrow(kion)
	library(ggplot2)
	library(GGally)
	ggpairs(iris, aes_string(colour="Species", alpha=0.5))