[R/SAS/Python]データの条件抽出②

目的
irisデータからSepal_Lengthが5.0cm以上のデータだけを抽出した以下のようなデータを作成したい。
(参考)Iris flower data set
https://en.wikipedia.org/wiki/Iris_flower_data_set

元データ

Sepal_LengthSepal_WidthPetal_LengthPetal_WidthSpecies
5.13.51.40.2setosa
4.931.40.2setosa
4.73.21.30.2setosa
4.63.11.50.2setosa
53.61.40.2setosa
5.43.91.70.4setosa
4.63.41.40.3setosa
53.41.50.2setosa
4.42.91.40.2setosa
4.93.11.50.1setosa
5.43.71.50.2setosa
4.83.41.60.2setosa
4.831.40.1setosa
4.331.10.1setosa
5.841.20.2setosa
5.74.41.50.4setosa
5.43.91.30.4setosa
5.13.51.40.3setosa
5.73.81.70.3setosa
5.13.81.50.3setosa
5.43.41.70.2setosa
5.13.71.50.4setosa
4.63.610.2setosa
5.13.31.70.5setosa
4.83.41.90.2setosa
531.60.2setosa
53.41.60.4setosa
5.23.51.50.2setosa
5.23.41.40.2setosa
4.73.21.60.2setosa
4.83.11.60.2setosa
5.43.41.50.4setosa
5.24.11.50.1setosa
5.54.21.40.2setosa
4.93.11.50.2setosa
53.21.20.2setosa
5.53.51.30.2setosa
4.93.61.40.1setosa
4.431.30.2setosa
5.13.41.50.2setosa
53.51.30.3setosa
4.52.31.30.3setosa
4.43.21.30.2setosa
53.51.60.6setosa
5.13.81.90.4setosa
4.831.40.3setosa
5.13.81.60.2setosa
4.63.21.40.2setosa
5.33.71.50.2setosa
53.31.40.2setosa
73.24.71.4versicolor
6.43.24.51.5versicolor
6.93.14.91.5versicolor
5.52.341.3versicolor
6.52.84.61.5versicolor
5.72.84.51.3versicolor
6.33.34.71.6versicolor
4.92.43.31versicolor
6.62.94.61.3versicolor
5.22.73.91.4versicolor
523.51versicolor
5.934.21.5versicolor
62.241versicolor
6.12.94.71.4versicolor
5.62.93.61.3versicolor
6.73.14.41.4versicolor
5.634.51.5versicolor
5.82.74.11versicolor
6.22.24.51.5versicolor
5.62.53.91.1versicolor
5.93.24.81.8versicolor
6.12.841.3versicolor
6.32.54.91.5versicolor
6.12.84.71.2versicolor
6.42.94.31.3versicolor
6.634.41.4versicolor
6.82.84.81.4versicolor
6.7351.7versicolor
62.94.51.5versicolor
5.72.63.51versicolor
5.52.43.81.1versicolor
5.52.43.71versicolor
5.82.73.91.2versicolor
62.75.11.6versicolor
5.434.51.5versicolor
63.44.51.6versicolor
6.73.14.71.5versicolor
6.32.34.41.3versicolor
5.634.11.3versicolor
5.52.541.3versicolor
5.52.64.41.2versicolor
6.134.61.4versicolor
5.82.641.2versicolor
52.33.31versicolor
5.62.74.21.3versicolor
5.734.21.2versicolor
5.72.94.21.3versicolor
6.22.94.31.3versicolor
5.12.531.1versicolor
5.72.84.11.3versicolor
6.33.362.5virginica
5.82.75.11.9virginica
7.135.92.1virginica
6.32.95.61.8virginica
6.535.82.2virginica
7.636.62.1virginica
4.92.54.51.7virginica
7.32.96.31.8virginica
6.72.55.81.8virginica
7.23.66.12.5virginica
6.53.25.12virginica
6.42.75.31.9virginica
6.835.52.1virginica
5.72.552virginica
5.82.85.12.4virginica
6.43.25.32.3virginica
6.535.51.8virginica
7.73.86.72.2virginica
7.72.66.92.3virginica
62.251.5virginica
6.93.25.72.3virginica
5.62.84.92virginica
7.72.86.72virginica
6.32.74.91.8virginica
6.73.35.72.1virginica
7.23.261.8virginica
6.22.84.81.8virginica
6.134.91.8virginica
6.42.85.62.1virginica
7.235.81.6virginica
7.42.86.11.9virginica
7.93.86.42virginica
6.42.85.62.2virginica
6.32.85.11.5virginica
6.12.65.61.4virginica
7.736.12.3virginica
6.33.45.62.4virginica
6.43.15.51.8virginica
634.81.8virginica
6.93.15.42.1virginica
6.73.15.62.4virginica
6.93.15.12.3virginica
5.82.75.11.9virginica
6.83.25.92.3virginica
6.73.35.72.5virginica
6.735.22.3virginica
6.32.551.9virginica
6.535.22virginica
6.23.45.42.3virginica
5.935.11.8virginica


作成するデータ

Sepal_LengthSepal_WidthPetal_LengthPetal_WidthSpecies
5.13.51.40.2setosa
53.61.40.2setosa
5.43.91.70.4setosa
53.41.50.2setosa
5.43.71.50.2setosa
5.841.20.2setosa
5.74.41.50.4setosa
5.43.91.30.4setosa
5.13.51.40.3setosa
5.73.81.70.3setosa
5.13.81.50.3setosa
5.43.41.70.2setosa
5.13.71.50.4setosa
5.13.31.70.5setosa
531.60.2setosa
53.41.60.4setosa
5.23.51.50.2setosa
5.23.41.40.2setosa
5.43.41.50.4setosa
5.24.11.50.1setosa
5.54.21.40.2setosa
53.21.20.2setosa
5.53.51.30.2setosa
5.13.41.50.2setosa
53.51.30.3setosa
53.51.60.6setosa
5.13.81.90.4setosa
5.13.81.60.2setosa
5.33.71.50.2setosa
53.31.40.2setosa
73.24.71.4versicolor
6.43.24.51.5versicolor
6.93.14.91.5versicolor
5.52.341.3versicolor
6.52.84.61.5versicolor
5.72.84.51.3versicolor
6.33.34.71.6versicolor
6.62.94.61.3versicolor
5.22.73.91.4versicolor
523.51versicolor
5.934.21.5versicolor
62.241versicolor
6.12.94.71.4versicolor
5.62.93.61.3versicolor
6.73.14.41.4versicolor
5.634.51.5versicolor
5.82.74.11versicolor
6.22.24.51.5versicolor
5.62.53.91.1versicolor
5.93.24.81.8versicolor
6.12.841.3versicolor
6.32.54.91.5versicolor
6.12.84.71.2versicolor
6.42.94.31.3versicolor
6.634.41.4versicolor
6.82.84.81.4versicolor
6.7351.7versicolor
62.94.51.5versicolor
5.72.63.51versicolor
5.52.43.81.1versicolor
5.52.43.71versicolor
5.82.73.91.2versicolor
62.75.11.6versicolor
5.434.51.5versicolor
63.44.51.6versicolor
6.73.14.71.5versicolor
6.32.34.41.3versicolor
5.634.11.3versicolor
5.52.541.3versicolor
5.52.64.41.2versicolor
6.134.61.4versicolor
5.82.641.2versicolor
52.33.31versicolor
5.62.74.21.3versicolor
5.734.21.2versicolor
5.72.94.21.3versicolor
6.22.94.31.3versicolor
5.12.531.1versicolor
5.72.84.11.3versicolor
6.33.362.5virginica
5.82.75.11.9virginica
7.135.92.1virginica
6.32.95.61.8virginica
6.535.82.2virginica
7.636.62.1virginica
7.32.96.31.8virginica
6.72.55.81.8virginica
7.23.66.12.5virginica
6.53.25.12virginica
6.42.75.31.9virginica
6.835.52.1virginica
5.72.552virginica
5.82.85.12.4virginica
6.43.25.32.3virginica
6.535.51.8virginica
7.73.86.72.2virginica
7.72.66.92.3virginica
62.251.5virginica
6.93.25.72.3virginica
5.62.84.92virginica
7.72.86.72virginica
6.32.74.91.8virginica
6.73.35.72.1virginica
7.23.261.8virginica
6.22.84.81.8virginica
6.134.91.8virginica
6.42.85.62.1virginica
7.235.81.6virginica
7.42.86.11.9virginica
7.93.86.42virginica
6.42.85.62.2virginica
6.32.85.11.5virginica
6.12.65.61.4virginica
7.736.12.3virginica
6.33.45.62.4virginica
6.43.15.51.8virginica
634.81.8virginica
6.93.15.42.1virginica
6.73.15.62.4virginica
6.93.15.12.3virginica
5.82.75.11.9virginica
6.83.25.92.3virginica
6.73.35.72.5virginica
6.735.22.3virginica
6.32.551.9virginica
6.535.22virginica
6.23.45.42.3virginica
5.935.11.8virginica

プログラム

RSASPythom
#ライブラリ呼び出し
library(dplyr)

#Sepal.Lengthが5以上のデータだけ抽出する
IRIS <- filter(iris,Sepal.Length >= 5)
data IRIS;
  set SASHELP.IRIS;
  if SepalLength >= 50 then output;
  else delete;
run;

SASではデータがcm単位ではなくmm単位なので50と指定しています。

#ライブラリ呼び出し
import pandas as pd
from sklearn.datasets import load_iris

#irisデータを呼び出してデータフレーム化する
iris = load_iris()
IRIS = pd.DataFrame(iris.data, columns = (["Sepal_Length", "Sepal_Width", "Petal_Length", "Petal_Width"]))
IRIS['species'] = iris.target_names[iris.target]

#Sepal_Lengthが5以上のデータだけ抽出する
IRIS2 = IRIS.query('Sepal_Length >= 5')



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