英文:
Proper notation for errors='ignore' with index clause in Pandas
问题
在另一个项目上工作今天。随着我的学习进展，情况要好得多，不过我正在尝试一些新东西。
我有一个数据框，它的性能非常出色。但是，我需要删除某些零件编号的行，因为它们与我的当前项目无关，我不想费力去筛选它们。目前表格中有大约112个这样的行，所以手动处理在我SQL数据库中的三个表格中将会非常耗时。目前我遇到了以下错误：
.....'KCB-0100T'）' 是无效的键
我认为这只是意味着它在表格中不存在。它并不总是存在，也不应该存在。在处理以下代码时，错误='ignore' 的正确形式是什么？
indexdf = df[(df['Part Number'] == 'KSA-9132',....).index
再往下一点，我有以下代码：
df.drop(indexdf, errors='ignore', axis=0, inplace=True)
但似乎在它达到那一点之前就抛出了错误。
英文:
working on another project today. It's going a lot better as I'm learning more, however I'm trying something new.
I have a dataframe that is performing excellently. However, I need it to drop rows of certain part numbers, as they are unrelated to my current project and I don't want to pick through them. There's about 112 in the sheet right now, so doing it manually would be incredibly time-consuming across the three sheets that get added to my SQL database. Right now I get the error
.....'KCB-0100T')' is an invalid key
Which I believe just means it doesn't exist in the sheet. It wont all the time, and isn't supposed to. What's the proper form for errors='ignore' when it comes to
indexdf = df[(df['Part Number'] == 'KSA-9132',....).index
A Little lower I have
df.drop(indexdf, errors='ignore',axis=0,inplace=True)
But it seems to throw the error before it even gets to that point.
答案1
得分: 0
尝试使用掩码和isin函数：
# 将要删除的零件号添加到这个列表中
part_numbers_to_drop = ['KSA-9132', 'KCB-0100T', ...]
# 使用isin()创建一个布尔掩码
mask = df['零件号'].isin(part_numbers_to_drop)
# 删除掩码为True的行
df.drop(df[mask].index, inplace=True)
英文:
Try this using a mask and isin:
# Add the part numbers you want to drop to this list
part_numbers_to_drop = ['KSA-9132', 'KCB-0100T', ...]
# Use isin() to create a boolean mask
mask = df['Part Number'].isin(part_numbers_to_drop)
# Drop the rows the mask
df.drop(df[mask].index, inplace=True)
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