#目的：讀入鳶尾花資料集

#1.載入tensorflow（含keras）等函數庫
import numpy as np
import pandas as pd
import tensorflow as tf

#2..載入鳶尾花資料集（讀入自己電腦硬碟的csv檔案）
#在colaboratory的python讀入自己的個人電腦硬碟裡的iris_data.csv
####################################上傳iris_data.csv
from google.colab import files
uploaded = files.upload()
for fn in uploaded.keys():
  print('User uploaded file "{name}" with length {length} bytes'.format(
      name=fn, length=len(uploaded[fn])))
# 確認iris_data.csv是否已上載
!ls *.* -l
##########################

#3.把csv檔案讀入成dataframe結構資料（use Pandas to read iris_data.csv）
df = pd.read_csv("./iris_data.csv")

# 載入資料集
target_mapping = {"setosa": 0,
          "versicolor": 1,
          "virginica": 2}
Y = df["target"].map(target_mapping)

# 使用Matplotlib顯示視覺化圖表
import matplotlib.pyplot as plt
colmap = np.array(["r", "g", "y"])
plt.figure(figsize=(10,5))
plt.subplot(1, 2, 1)
plt.subplots_adjust(hspace = .5)
plt.scatter(df["sepal_length"], df["sepal_width"], color=colmap[Y])
plt.xlabel("Sepal Length")
plt.ylabel("Sepal Width")
plt.subplot(1, 2, 2)
plt.scatter(df["petal_length"], df["petal_width"], color=colmap[Y])
plt.xlabel("Petal Length")
plt.ylabel("Petal Width")
plt.show()

# 使用Seaborn顯示視覺化圖表
import seaborn as sns
sns.pairplot(df, hue="target")