數(shù)據(jù)準(zhǔn)備

import pandas as pd


product_info = {
    "訂單號(hào)": [ "2951110000099262111", "2181910000909928191", "2194560000121355545", "1194560000121311126", "1483160000121315483"],
    "數(shù)量": [92, 61, 66, 33, 15],
    "價(jià)格(USD)": [230, 122, 150, 190, 200],
    "狀態(tài)": ["Not Delivered", "Not Delivered", "Not Delivered", "Not Shipped", "Not Delivered"],
    "訂單日期": ["2022-02-12", "2022-03-02", "2022-01-22", "2022-02-22", "2022-02-15"],
    "訂單編號(hào)": ["444111", "444122", "444132", "444003", "444244"],
}

df = pd.DataFrame(product_info, index=['one', 'two', 'three', 'four', 'five'])
print(df)
'''
                       訂單號(hào)  數(shù)量  價(jià)格(USD)             狀態(tài)        訂單日期    訂單編號(hào)
one    2951110000099262111  92      230  Not Delivered  2022-02-12  444111
two    2181910000909928191  61      122  Not Delivered  2022-03-02  444122
three  2194560000121355545  66      150  Not Delivered  2022-01-22  444132
four   1194560000121311126  33      190    Not Shipped  2022-02-22  444003
five   1483160000121315483  15      200  Not Delivered  2022-02-15  444244
'''

方法介紹

按columns過濾

全列名過濾

# 過濾出列名為“訂單號(hào)”和“訂單編號(hào)”列
res_df = df.filter(items=["訂單號(hào)", '訂單編號(hào)'])
print(res_df)
'''
                       訂單號(hào)    訂單編號(hào)
one    2951110000099262111  444111
two    2181910000909928191  444122
three  2194560000121355545  444132
four   1194560000121311126  444003
five   1483160000121315483  444244
'''

模糊過濾

# 過濾出列名中包含“訂單”的所有列
res_df = df.filter(like='訂單', axis=1)
print(res_df)
'''
                       訂單號(hào)        訂單日期    訂單編號(hào)
one    2951110000099262111  2022-02-12  444111
two    2181910000909928191  2022-03-02  444122
three  2194560000121355545  2022-01-22  444132
four   1194560000121311126  2022-02-22  444003
five   1483160000121315483  2022-02-15  444244
'''

正則過濾

# 過濾出以"訂單"開頭的所有列
res_df = df.filter(regex='^訂單', axis=1)
print(res_df)
'''
                       訂單號(hào)        訂單日期    訂單編號(hào)
one    2951110000099262111  2022-02-12  444111
two    2181910000909928191  2022-03-02  444122
three  2194560000121355545  2022-01-22  444132
four   1194560000121311126  2022-02-22  444003
five   1483160000121315483  2022-02-15  444244
'''

按index過濾

全名稱過濾

# 過濾出index為"one", "four"的行
res_df = df.filter(items=["one", 'four'], axis=0)
print(res_df)
'''
                      訂單號(hào)  數(shù)量  價(jià)格(USD)             狀態(tài)        訂單日期    訂單編號(hào)
one   2951110000099262111  92      230  Not Delivered  2022-02-12  444111
four  1194560000121311126  33      190    Not Shipped  2022-02-22  444003
'''

模糊過濾

# 過濾出index包含"e"的所有行
res_df = df.filter(like='e', axis=0)
print(res_df)
'''
                       訂單號(hào)  數(shù)量  價(jià)格(USD)             狀態(tài)        訂單日期    訂單編號(hào)
one    2951110000099262111  92      230  Not Delivered  2022-02-12  444111
three  2194560000121355545  66      150  Not Delivered  2022-01-22  444132
five   1483160000121315483  15      200  Not Delivered  2022-02-15  444244
'''

正則過濾

# 過濾出以"t"開頭的所有行
res_df = df.filter(regex='^t', axis=0)
print(res_df)
'''
                       訂單號(hào)  數(shù)量  價(jià)格(USD)             狀態(tài)        訂單日期    訂單編號(hào)
two    2181910000909928191  61      122  Not Delivered  2022-03-02  444122
three  2194560000121355545  66      150  Not Delivered  2022-01-22  444132
'''

多條件過濾

# 過濾出以"價(jià)格"開頭或名稱為"訂單號(hào)"的所有列
res_df = df.filter(regex='^價(jià)格|訂單號(hào)', axis=1)
print(res_df)
'''
               訂單號(hào)  價(jià)格（USD）
0  295111000262111      230
1  218191000928191      122
2   21945600355545      150
3   11945600311126      190
4   14831600315483      200
'''

# 過濾出以"t"開頭或以"f"開頭的所有行
res_df = df.filter(regex='^t|^f', axis=0)
print(res_df)
'''
                       訂單號(hào)  數(shù)量  價(jià)格(USD)             狀態(tài)        訂單日期    訂單編號(hào)
two    2181910000909928191  61      122  Not Delivered  2022-03-02  444122
three  2194560000121355545  66      150  Not Delivered  2022-01-22  444132
four   1194560000121311126  33      190    Not Shipped  2022-02-22  444003
five   1483160000121315483  15      200  Not Delivered  2022-02-15  444244
'''