blocks|key|3337859|text|您可以过滤它们并在Python+3中像这样计算统计数据：|type|unstyled|depth|inlineStyleRanges|entityRanges|data|3337860|import+csv

total,+survived+=+0,+0

with+open('titanic-new_alphabetized.csv',++newline='')+as+csvfile:
++++for+row+in+filter(lambda+p:+'male'==p[3],+csv.reader(csvfile,+delimiter=+',')):
++++++++total+%2B=+1
++++++++if+int(row[0]):
++++++++++++survived+%2B=+1

print('total:+{},+survived:+{}+({:.2f}%25)'.format(total,+survived,+
+++++++++++++++++++++++++++++++++++++++++++++++++survived/total+*+100))|code-block|syntax|javascript|3337861|输出：|3337862|total:+577,+survived:+109+(18.89%25)|3337863|entityMap^0|0|0|0|0^^$0|@$1|2|3|4|5|6|7|M|8|@]|9|@]|A|$]]|$1|B|3|C|5|D|7|N|8|@]|9|@]|A|$E|F]]|$1|G|3|H|5|6|7|O|8|@]|9|@]|A|$]]|$1|I|3|J|5|D|7|P|8|@]|9|@]|A|$E|F]]|$1|K|3|-4|5|6|7|Q|8|@]|9|@]|A|$]]]|L|$]]

You could filter them and compute the statistic like this in Python 3:

<pre><code>import csv

total, survived = 0, 0

with open('titanic-new_alphabetized.csv', newline='') as csvfile:
 for row in filter(lambda p: 'male'==p[3], csv.reader(csvfile, delimiter= ',')):
 total += 1
 if int(row[0]):
 survived += 1

print('total: {}, survived: {} ({:.2f}%)'.format(total, survived, 
 survived/total * 100))
</code></pre>

Output:

<pre class="lang-none prettyprint-override"><code>total: 577, survived: 109 (18.89%)
</code></pre>

blocks|key|2925444|text|您正在使用list语法创建字典。|type|unstyled|depth|inlineStyleRanges|offset|length|style|CODE|entityRanges|data|2925445|您应该使用dict+=+{}。|2925446|entityMap^0|5|4|0|0^^$0|@$1|2|3|4|5|6|7|J|8|@$9|K|A|L|B|C]]|D|@]|E|$]]|$1|F|3|G|5|6|7|M|8|@]|D|@]|E|$]]|$1|H|3|-4|5|6|7|N|8|@]|D|@]|E|$]]]|I|$]]

You are creating your dictionary using the <code>list</code> syntax.

You should use dict = {}

blocks|key|2345743|text|您还应该以变量的形式打开文件，这样以后就可以轻松地关闭它。|type|unstyled|depth|inlineStyleRanges|entityRanges|data|2345744|或者使用with+...+as打开文件。|offset|length|style|CODE|2345745|entityMap^0|0|4|B|0^^$0|@$1|2|3|4|5|6|7|J|8|@]|9|@]|A|$]]|$1|B|3|C|5|6|7|K|8|@$D|L|E|M|F|G]]|9|@]|A|$]]|$1|H|3|-4|5|6|7|N|8|@]|9|@]|A|$]]]|I|$]]

You should also open the file as a variable, so you can close it easily later.

Or use <code>with ... as</code> to open files.

blocks|key|3337787|text|您可以尝试这样做，首先删除空列表，然后筛选列表以获得百分比：|type|unstyled|depth|inlineStyleRanges|entityRanges|data|3337788|import+csv

reader+=+csv.reader(open('1.csv'),+delimiter=',')

data+=+filter(lambda+p:+p,+list(reader))+#+remove+empty+list
filtered=filter(lambda+p:+p[0]=='0'+and+p[3]+==+'male',+data)

print(len(filtered)*1.0/len(data))|code-block|syntax|javascript|3337789|结果|3337790|0.525252525253|3337791|entityMap^0|0|0|0|0^^$0|@$1|2|3|4|5|6|7|M|8|@]|9|@]|A|$]]|$1|B|3|C|5|D|7|N|8|@]|9|@]|A|$E|F]]|$1|G|3|H|5|6|7|O|8|@]|9|@]|A|$]]|$1|I|3|J|5|D|7|P|8|@]|9|@]|A|$E|F]]|$1|K|3|-4|5|6|7|Q|8|@]|9|@]|A|$]]]|L|$]]

You can try this, remove the empty list first and then filter the list to get the percentage:

<pre><code>import csv

reader = csv.reader(open('1.csv'), delimiter=',')

data = filter(lambda p: p, list(reader)) # remove empty list
filtered=filter(lambda p: p[0]=='0' and p[3] == 'male', data)

print(len(filtered)*1.0/len(data))
</code></pre>

Result 

<pre><code>0.525252525253
</code></pre>

blocks|key|3337809|text|您可以使用csv.DictReader()将您的csv读入一个dict列表(在这里，我已经将列名命名为c1，c2)。因为我不确定它们的意义)。|type|unstyled|depth|inlineStyleRanges|entityRanges|data|3337810|有了它，您就可以使用列表理解来迭代该日期并检查男性的条目，并将生存日期输入list+men。|offset|length|style|CODE|3337811|现在你可以找到那些没有活下来的人(假设“0”表示死亡，“1”表示活着)。|3337812|import+csv
with+open('names.csv')+as+file:
++++reader+=+csv.DictReader(file,+delimiter=+',',fieldnames=['c1','c2','c3','c4','c5','c6','c7'])
++++#print+reader+#+[{'c3':+'Abbing,+Mr.+Anthony',+'c2':+'3',+'c1':+'0',+'c7':+'7.55',+'c6':+'C.A.+5547',+'c5':+'42',+'c4':+'male'},+{'c3':+'',+'c2':+'',+'c1':+'',+'c7':+'',+'c6':+'',+'c5':+'',+'c4':+''},+{'c3':+'Abbott,+Mr.+Rossmore+Edward',+'c2':+'3',+'c1':+'0',+'c7':+'20.25',+'c6':+'C.A.+2673',+'c5':+'16',+'c4':+'male'}...]
++++men+=+[each['c1']+for+each+in+reader+if+each['c4']=='male']
++++#print+men+#['0',+'0',+'0',+'0',+'1'...]
++++print+men.count('0')*100/len(men)
input('press+ENTER+to+exit')|code-block|syntax|javascript|3337813|entityMap^0|0|16|3|0|0|0^^$0|@$1|2|3|4|5|6|7|Q|8|@]|9|@]|A|$]]|$1|B|3|C|5|6|7|R|8|@$D|S|E|T|F|G]]|9|@]|A|$]]|$1|H|3|I|5|6|7|U|8|@]|9|@]|A|$]]|$1|J|3|K|5|L|7|V|8|@]|9|@]|A|$M|N]]|$1|O|3|-4|5|6|7|W|8|@]|9|@]|A|$]]]|P|$]]

You can use csv.DictReader() to read your csv as a list of dict(here i have given the column names as c1,c2.. as I aint sure of their significance). 

With that in hand, you can use list comprehension to iterate through the date and check for entries of male and get the survival date into list <code>men</code>

Now you can find the average of men who didnt survive(assuming '0' signifies dead and '1' for alive)

<pre><code>import csv
with open('names.csv') as file:
 reader = csv.DictReader(file, delimiter= ',',fieldnames=['c1','c2','c3','c4','c5','c6','c7'])
 #print reader # [{'c3': 'Abbing, Mr. Anthony', 'c2': '3', 'c1': '0', 'c7': '7.55', 'c6': 'C.A. 5547', 'c5': '42', 'c4': 'male'}, {'c3': '', 'c2': '', 'c1': '', 'c7': '', 'c6': '', 'c5': '', 'c4': ''}, {'c3': 'Abbott, Mr. Rossmore Edward', 'c2': '3', 'c1': '0', 'c7': '20.25', 'c6': 'C.A. 2673', 'c5': '16', 'c4': 'male'}...]
 men = [each['c1'] for each in reader if each['c4']=='male']
 #print men #['0', '0', '0', '0', '1'...]
 print men.count('0')*100/len(men)
input('press ENTER to exit')
</code></pre>

So I have a csv (<a href="https://ufile.io/y4nr9" rel="nofollow noreferrer">https://ufile.io/y4nr9</a>) which is seperated by ',' and contain columns such as: 'name','survived','sex' etc. I want to find the percentage of males that didnt survive and print the statistic. Here is my code so far:

<pre><code>import csv
reader = csv.reader(open('titanic-new_alphabetized.csv'), delimiter= ',')
filtered = filter(lambda p: 'male' == p[3], reader)
dict = []

input('press ENTER to exit')
</code></pre>

How to filter two columns in a csv?

翻译质量差，导致语言生硬或混乱。

没有提供实际的解决方法或示例。

解答不清晰，无法理解或解决问题。

页面排版不美观，阅读体验差。

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因此，我有一个csv ()，它由“，”分隔，并包含“名称”、“幸存”、“性别”等列。我想找出没有存活的男性的百分比，并打印统计数据。到目前为止，我的代码如下：import csvreader = csv.reader(open('titanic-new_alphabetized.csv'), delimiter= ',')filtered = filter(lambda p: 'male' == 

问如何过滤csv中的两列？
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问如何过滤csv中的两列？
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