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pandas - 在熊猫中将时间戳转换为to_date

问题描述

输入我正在为 sql 查询类型构建和应用程序，我能够生成它，但接收时间戳格式的输出，请帮助将其转换为 to_date 格式。这是我的代码：-

from pandas import *
table_name="ADI"
file_name=pandas.read_excel('supermarke.xlsx')    
def SQL_Insert(SOURCE, TARGET):
    sql_texts = []
    for index, row in SOURCE.iterrows():
        sql_texts.append(
            'INSERT INTO ' + TARGET + ' (' + str(', '.join(SOURCE.columns)) + ')   VALUES ' + str(tuple(row.values))+";")

    return ('\n'.join(sql_texts))
print(SQL_Insert(file_name, table_name))

这是我得到的输出：-

INSERT INTO ADI (ID, Address, City, State, Country, Supermarket Name, Number of Employees, DATE)   VALUES (1, '3666 21st St', 'San Francisco', 'CA 94114', 'USA', 'Madeira', 8, Timestamp('2018-01-12 00:00:00'));
INSERT INTO ADI (ID, Address, City, State, Country, Supermarket Name, Number of Employees, DATE)   VALUES (2, '735 Dolores St', 'San Francisco', 'CA 94119', 'USA', 'Bready Shop', 15, Timestamp('2018-01-12 00:00:00'));
INSERT INTO ADI (ID, Address, City, State, Country, Supermarket Name, Number of Employees, DATE)   VALUES (3, '332 Hill St', 'San Francisco', 'California 94114', 'USA', 'Super River', 25, Timestamp('2018-01-12 00:00:00'));
INSERT INTO ADI (ID, Address, City, State, Country, Supermarket Name, Number of Employees, DATE)   VALUES (4, '3995 23rd St', 'San Francisco', 'CA 94114', 'USA', "Ben's Shop", 10, Timestamp('2018-01-12 00:00:00'));

这是我所期待的：-

INSERT INTO ADI (ID, Address, City, State, Country, Supermarket Name, Number of Employees, DATE)   VALUES (1, '3666 21st St', 'San Francisco', 'CA 94114', 'USA', 'Madeira', 8,  TO_DATE('12/01/2018 00:00:00', 'MM/DD/YYYY HH24:MI:SS');
INSERT INTO ADI (ID, Address, City, State, Country, Supermarket Name, Number of Employees, DATE)   VALUES (2, '735 Dolores St', 'San Francisco', 'CA 94119', 'USA', 'Bready Shop', 15, TO_DATE('12/01/2018 00:00:00', 'MM/DD/YYYY HH24:MI:SS');
INSERT INTO ADI (ID, Address, City, State, Country, Supermarket Name, Number of Employees, DATE)   VALUES (3, '332 Hill St', 'San Francisco', 'California 94114', 'USA', 'Super River', 25,TO_DATE('12/01/2018 00:00:00', 'MM/DD/YYYY HH24:MI:SS');
INSERT INTO ADI (ID, Address, City, State, Country, Supermarket Name, Number of Employees, DATE)   VALUES (4, '3995 23rd St', 'San Francisco', 'CA 94114', 'USA', "Ben's Shop", 10, TO_DATE('12/01/2018 00:00:00', 'MM/DD/YYYY HH24:MI:SS');

请帮帮我

标签： pandas

解决方案

如果您必须手动将 SQL 查询字符串拼接在一起，请尝试此操作（未经测试，因为我没有您的数据）：

import pandas as pd
table_name = 'ADI'
df = pandas.read_excel('supermarke.xlsx')

def SQL_Insert(SOURCE, TARGET):
    sql_texts = []
    for index, row in SOURCE.iterrows():
        formatted_date = pd.to_datetime(row[-1]).strftime('%m/%d/%Y %H:%M:%S')
        date_str = 'TO_DATE(\'{}\', \'MM/DD/YYYY HH24:MI:SS\')'.format(formatted_date)

        sql_texts.append((
            'INSERT INTO ' + 
            TARGET + 
            ' (' + 
            str(', '.join(SOURCE.columns)) + ')   VALUES ' + 
            str(tuple(row.values[:-1])) + 
            date_str +
            ';'))

    return ('\n'.join(sql_texts))

print(SQL_Insert(df, table_name))

我建议不要手动构建查询字符串。这是一个已解决的问题。进一步阅读：如何从 SQLAlchemy 表达式中获取原始的编译 SQL 查询？

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