Python -在另一列中找到给定匹配字符串的列的平均值。
Python -在另一列中找到给定匹配字符串的列的平均值。
提问于 2018-02-18 11:40:19
我正在试图计算数据文件中包含来自wordlist的单词的产品数量，然后找出这些产品的平均价格。以下的尝试-
for word in wordlist:
total_count += dframe.Product.str.contains(word, case=False).sum()
total_price += dframe[dframe['Product'].str.contains(word)]['Price']
print(dframe[dframe['Product'].str.contains(word)]['Price'])
average_price = total_price / total_count将average_price作为Series([], Name: Price, dtype: float64)返回，而不是按预期返回浮点值。
我做错了什么？
谢谢!
回答 2
Stack Overflow用户
回答已采纳
发布于 2018-02-18 11:42:41
在标量值的每个条件下，需要列sum的Price：
total_count, total_price = 0, 0
for word in wordlist:
total_count += dframe.Product.str.contains(word, case=False).sum()
total_price += dframe.loc[dframe['Product'].str.contains(word), 'Price'].sum()
average_price = total_price / total_count或者chache mask用于变量以获得更好的可达性和性能：
total_count, total_price = 0, 0
for word in 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解决方案应该用regex word1|word2|word3 - | means or简化
mask = dframe.Product.str.contains('|'.join(wordlist), case=False)
total_count = mask.sum()
total_price = dframe.loc[mask, 'Price'].sum()
average_price = total_price / total_countmask = dframe.Product.str.contains('|'.join(wordlist), case=False)
average_price = dframe.loc[mask, 'Price'].mean()样本
dframe = pd.DataFrame({
'Product': ['a1','a2','a3','c1','c1','b','b2','c3','d2'],
'Price': [1,3,5,6,3,2,3,5,2]
})
print (dframe)
Price Product
0 1 a1
1 3 a2
2 5 a3
3 6 c1
4 3 c1
5 2 b
6 3 b2
7 5 c3
8 2 d2
wordlist = ['b','c']
mask = dframe.Product.str.contains('|'.join(wordlist), case=False)
average_price = dframe.loc[mask, 'Price'].mean()
print (average_price)
3.8Stack Overflow用户
发布于 2018-02-18 11:48:05
您可以使用value函数来避免级数。
total_count += dframe.Product.str.contains(word，case=False).value.sum()
dframedframe['Product'].str.contains(word).value total_price +=
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原文链接：
https://stackoverflow.com/questions/48851238
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