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測試環境為 CentOS 8 (虛擬機)
可以透過 select_dtypes 與 dtypes 函數來指定只顯示那種資料格式的欄位, Pandas 所使用的資料格式如下.
參考資料 – https://note.nkmk.me/en/python-pandas-dtype-astype/
- int8
8-bit signed integer
- int16
16-bit signed integer
- int32
32-bit signed integer
- int64
64-bit signed integer
- uint8
8-bit unsigned integer
- uint16
16-bit unsigned integer
- uint32
32-bit unsigned integer
- uint64
64-bit unsigned integer
- float16
16-bit floating-point number
- float32
32-bit floating-point number
- float64
64-bit floating-point number
- float128
128-bit floating-point number
- complex64
64-bit complex floating-point number
- complex128
128-bit complex floating-point number
- complex256
256-bit complex floating-point number
- bool
Boolean (True or False)
- unicode
Unicode string
- object
Python objects
安裝所需模組
[root@localhost ~]# pip install pandas
|
匯入模組
[root@localhost ~]# python3
Python 3.6.8 (default, Sep 10 2021, 09:13:53)
[GCC 8.5.0 20210514 (Red Hat 8.5.0-3)] on linux
Type "help", "copyright", "credits" or "license" for more information.
>>> import pandas as pd
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資料範例.
df = pd.DataFrame({
"Class":
{
"Ben": 'A1',
"Alex": 'A1',
"Jeff": 'B1',
"Dexter": 'B1'
},
"Chinese":
{
"Ben": 68,
"Alex": 86,
"Jeff": 57,
"Dexter": 95
},
"English":
{
"Ben": 63,
"Alex": 92,
"Jeff": 83,
"Dexter": 89
},
"Math":
{
"Ben": 65,
"Alex": 89,
"Jeff": 77,
"Dexter": 100
}
})
|
>>> df
Class Chinese English Math
Ben A1 68 63 65
Alex A1 86 92 89
Jeff B1 57 83 77
Dexter B1 95 89 100
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透過以下兩種方式.
select_dtypes
>>> df.select_dtypes(include=['int64','float64'])
Chinese English Math
Ben 68 63 65
Alex 86 92 89
Jeff 57 83 77
Dexter 95 89 100
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>>> list(df.select_dtypes(include=['int64','float64']))
['Chinese', 'English', 'Math']
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dtypes
>>> df.dtypes
Class object
Chinese int64
English int64
Math int64
dtype: object
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>>> df.columns
Index(['Class', 'Chinese', 'English', 'Math'], dtype='object')
>>> df.dtypes=='int64'
Class False
Chinese True
English True
Math True
dtype: bool
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>>> df.columns[df.dtypes=='int64']
Index(['Chinese', 'English', 'Math'], dtype='object')
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>>> list(df.columns[df.dtypes=='int64'])
['Chinese', 'English', 'Math']
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