pandas基礎運算和合併示例

,"source":[
"### python資料分析的三劍客"]}
,,"outputs":[
],"source":[
"import numpy as np\n"
,"\n"
,"import pandas as pd\n"
,"\n"
,"# pip install matplotlib\n"
,"# 畫圖，視覺化！\n"
,"# 頭號玩家，虛擬實境遊戲，視覺化，立體化\n"
,"import matplotlib.pyplot as plt"]}
,,"source":[
"### 生成物件"]}
,,"outputs":[
,"execution_count":3
,"metadata":,
"output_type"
:"execute_result"}]
,"source":[
"# 一維的\n"
,"s = pd.series(data = [88,103,68,134,99],index = ['張三','李四','王五','老路','jack'],\n"
," dtype=np.float32,name = 'python')\n"
,"s"]}
,,"outputs":[
,"execution_count":9
,"metadata":,
"output_type"
:"execute_result"}]
,"source":[
"df = pd.dataframe(data = np.random.randint(0,150,size=(5,3)),\n"
," index = ['張三','李四','王五','老路','jack'],\n"
," columns=['python','en','數學'])\n"
,"df"]}
,,"source":[
"### 檢視資料"]}
,,"outputs":[
,"execution_count":11
,"metadata":,
"output_type"
:"execute_result"}]
,"source":[
"s['王五']"]}
,,"outputs":[
,"execution_count":13
,"metadata":,
"output_type"
:"execute_result"}]
,"source":[
"df.head(3)"]}
,,"outputs":[
,"execution_count":14
,"metadata":,
"output_type"
:"execute_result"}]
,"source":[
"df.tail(3)"]}
,,"source":[
"### 選擇"]}
,,"outputs":[
],"source":[
"df['張三','王五']"]}
,,"outputs":[
,"execution_count":20
,"metadata":,
"output_type"
:"execute_result"}]
,"source":[
"# 列索引\n"
,"df[['python','en']]"]}
,,"outputs":[
,"execution_count":24
,"metadata":,
"output_type"
:"execute_result"}]
,"source":[
"df[0::2]"]}
,,"outputs":[
,"execution_count":27
,"metadata":,
"output_type"
:"execute_result"}]
,"source":[
"# 檢索行索引\n"
,"df.loc[['張三','jack']]"]}
,,"outputs":[
,"execution_count":29
,"metadata":,
"output_type"
:"execute_result"}]
,"source":[
"# 檢索行，可以使用iloc\n"
,"# 帶有i，數字0,1,2,3\n"
,"df.iloc[[0,4]]"]}
,,"outputs":[
,"execution_count":30
,"metadata":,
"output_type"
:"execute_result"}]
,"source":[
"# 資料庫中，存著不同人的成績，需要獲取資料庫中，張三，jack的python和數學成績\n"
,"# ？？？sql，你在腦子，想一下\n"
,"# pandas比sql簡單。\n"
,"df[['python','數學']].loc[['張三','jack']]"]}
,,"source":[
"### 缺失值"]}
,,"outputs":[
,"execution_count":38
,"metadata":,
"output_type"
:"execute_result"}]
,"source":[
"# pandas中的缺失值，使用nan表示，nan：not a number\n"
,"cond = df >= 31\n"
,"df2 = df[cond]\n"
,"df2"]}
,,"outputs":[
,"execution_count":36
,"metadata":,
"output_type"
:"execute_result"}]
,"source":[
"# 填充空值，fillna呼叫，返回\n"
,"df2.fillna(60)"]}
,,"outputs":[
,"execution_count":39
,"metadata":,
"output_type"
:"execute_result"}]
,"source":[
"df2"]}
,,"outputs":[
,"execution_count":40
,"metadata":,
"output_type"
:"execute_result"}]
,"source":[
"# dropna刪除空值\n"
,"df2.dropna()"]}
,,"outputs":[
,"execution_count":41
,"metadata":,
"output_type"
:"execute_result"}]
,"source":[
"# axis 軸，座標：x軸，y軸\n"
,"# dataframe二維的：行（0），列（1）\n"
,"df2.dropna(axis = 0 )"]}
,,"outputs":[
,"execution_count":43
,"metadata":,
"output_type"
:"execute_result"}]
,"source":[
"df2"]}
,,"outputs":[
,"execution_count":42
,"metadata":,
"output_type"
:"execute_result"}]
,"source":[
"df2.dropna(axis = 1)"]}
],"metadata":,
"language_info":,
"file_extension"
:".py"
,"mimetype"
:"text/x-python"
,"name"
:"python"
,"nbconvert_exporter"
:"python"
,"pygments_lexer"
:"ipython3"
,"version"
:"3.8.1"}}
,"nbformat":4
,"nbformat_minor":4
}

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