pandas to_sql在重复的主键上失败 [英] Pandas to_sql fails on duplicate primary key

问题描述

我想使用pandas df.to_sql()函数追加到现有表中.

I'd like to append to an existing table, using pandas df.to_sql() function.

我设置了if_exists='append'，但是我的表有主键.

I set if_exists='append', but my table has primary keys.

在尝试对现有表进行append时，我想做与insert ignore等效的操作，因此我将避免重复的输入错误.

I'd like to do the equivalent of insert ignore when trying to append to the existing table, so I would avoid a duplicate entry error.

大熊猫有可能吗?还是我需要写一个明确的查询?

Is this possible with pandas, or do I need to write an explicit query?

推荐答案

很遗憾，没有选项可以指定"INSERT IGNORE".这就是我克服的限制，可以在数据库中插入不重复的行(数据帧名称为df)

There is unfortunately no option to specify "INSERT IGNORE". This is how I got around that limitation to insert rows into that database that were not duplicates (dataframe name is df)

for i in range(len(df)):
    try:
        df.iloc[i:i+1].to_sql(name="Table_Name",if_exists='append',con = Engine)
    except IntegrityError:
        pass #or any other action

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