pandas Python - ValueError：无法索引包含 NA / NaN 值的向量
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Python - ValueError: Cannot index with vector containing NA / NaN values
提问by harry04
I'm trying to get the average price of products containing any substrings from a wordlist from a dataframe. I've been able to do so with the following code on multiple spreadsheets -
我试图从数据帧的单词列表中获取包含任何子字符串的产品的平均价格。我已经能够在多个电子表格上使用以下代码来做到这一点 -
dframe['Product'].fillna('', inplace=True)
dframe['Price'].fillna(0, inplace=True)
total_count = 0
total_price = 0
for word in ransomware_wordlist:
mask = dframe.Product.str.contains(word, case=False)
total_count += mask.sum()
total_price += dframe.loc[mask, 'Price'].sum()
average_price = total_price / total_count
print(average_price)
However, one of the spreadsheets throws an error at line -
但是，其中一个电子表格在行处引发错误 -
dframe['Product'].fillna('', inplace=True)
with
和
ValueError: cannot index with vector containing NA / NaN values
I fail to understand why dframe['Product'].fillna('', inplace=True)isn't handling this problem.
我不明白为什么dframe['Product'].fillna('', inplace=True)不处理这个问题。
In desperate need of some help! Thanks!
迫切需要一些帮助！谢谢！
回答by jezrael
If first line failed still is possible replace NaNs in condition in str.containsby parameter na=False:
如果第一行仍然失败，则可以通过参数替换NaN条件中str.contains的s na=False：
mask = dframe.Product.str.contains(word, case=False, na=False)
Or try omit inplace=Trueand assign back:
或者尝试省略inplace=True并重新分配：
dframe['Product'] = dframe['Product'].fillna('')
