<jupyter_start><jupyter_text>練習時間觀察有興趣的欄位的資料分佈，並嘗試找出有趣的訊息 Eg- 計算任意欄位的平均數及標準差- 畫出任意欄位的[直方圖](https://zh.wikipedia.org/zh-tw/%E7%9B%B4%E6%96%B9%E5%9B%BE) Hints:- [Descriptive Statistics For pandas Dataframe](https://chrisalbon.com/python/data_wrangling/pandas_dataframe_descriptive_stats/)- [pandas 中的繪圖函數](https://amaozhao.gitbooks.io/pandas-notebook/content/pandas%E4%B8%AD%E7%9A%84%E7%BB%98%E5%9B%BE%E5%87%BD%E6%95%B0.html)<jupyter_code># Show numeric datatype in DataFrame

app_train.select_dtypes(exclude=["object"]).iloc[:5, :8]
# Exploratory Data Analysis (EDA) by column AMT_INCOME_TOTAL

AMT_INCOME_TOTAL = app_train["AMT_INCOME_TOTAL"]

print("AMT_INCOME_TOTAL - mean: {0:.2f}".format(AMT_INCOME_TOTAL.mean()))
print("AMT_INCOME_TOTAL - std: {0:.2f}".format(AMT_INCOME_TOTAL.std()))

AMT_INCOME_TOTAL.describe().astype("int")
# Display histogram by column AMT_INCOME_TOTAL

histogram_kwargs = {
    "title": "AMT INCOME TOTAL",
    "kind": "hist", 
    "bins": 40, 
    "color": "g", 
    "edgecolor": "black", 
    "linewidth": 1.2, 
    "alpha": 0.6,
    "figsize": (15, 8)
}

histogram_lables = {
    "xlabel": "Income",
    "ylabel": "Frequency"
}

data_number = 1000

ax = AMT_INCOME_TOTAL[:data_number].plot(**histogram_kwargs)
ax.set(**histogram_lables)

plt.show()<jupyter_output><empty_output>
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{'chain_length': '1', 'dir': 'jupyter-structured-clean-dedup', 'id': '217467', 'license': 'MIT', 'n_tokens_mistral': 683, 'n_tokens_neox': 640, 'n_words': 71, 'path': 'homework/Day_005_HW.ipynb', 'repo_name': 'hackerYM/2nd-ML100Days', 'size': '1309'}