Question

我想使用DecisionTree 2.2.2来构建决策树。 https://engineering.purdue.edu/kak/distDT/DecisionTree-2.2.2.html

然而，它使用这种奇怪的csv格式。

"","pgtime","pgstat","age","eet","g2","grade","gleason","ploidy"
"1",6.1,0,64,2,10.26,2,4,"diploid"
"2",9.4,0,62,1,NA,3,8,"aneuploid"
"3",5.2,1,59,2,9.99,3,7,"diploid"
"4",3.2,1,62,2,3.57,2,4,"diploid"
"5",1.9,1,64,2,22.56,4,8,"tetraploid"
"6",4.8,0,69,1,6.14,3,7,"diploid"
"7",5.8,0,75,2,13.69,2,NA,"tetraploid"
"8",7.3,0,71,2,NA,3,7,"aneuploid"
"9",3.7,1,73,2,11.77,3,6,"diploid"

第一行，第一个元素应为＆＃34;＆＃34;
应引用标题名称。
应引用索引列。
应引用所有符号功能。

我的问题是如何使用pandas to_csv函数将DataFrame保存为这种格式？如果不可能，你能建议什么是最好的解决方案？

谢谢

这是我尝试过的。我将我的列转换为字符串类型：

df.col1 = df.col1.apply(str)

并在保存时使用index_label：

df.to_csv( 'filename.csv', header=True, index=True, index_label='"')

但这给了我以下内容：

"""",url,class,length,volume,name,degree,pagerank
......

第一个元素是四个引号。

Answer 1

首先，只是为了证明在中阅读是正常的：

In [11]: df = pd.read_clipboard(sep=',', index_col=0) In [12]: df Out[12]: pgtime pgstat age eet g2 grade gleason ploidy 1 6.1 0 64 2 10.26 2 4 diploid 2 9.4 0 62 1 NaN 3 8 aneuploid 3 5.2 1 59 2 9.99 3 7 diploid 4 3.2 1 62 2 3.57 2 4 diploid 5 1.9 1 64 2 22.56 4 8 tetraploid 6 4.8 0 69 1 6.14 3 7 diploid 7 5.8 0 75 2 13.69 2 NaN tetraploid 8 7.3 0 71 2 NaN 3 7 aneuploid 9 3.7 1 73 2 11.77 3 6 diploid

输出csv时必须使用quoting=csv.QUOTING_NONNUMERIC *

In [21]: s = StringIO() In [22]: df.to_csv(s, quoting=2) # or output to file instead In [23]: s.getvalue() Out[23]: '"","pgtime","pgstat","age","eet","g2","grade","gleason","ploidy"\n1,6.1,0,64,2,10.26,2,4.0,"diploid"\n2,9.4,0,62,1,"",3,8.0,"aneuploid"\n3,5.2,1,59,2,9.99,3,7.0,"diploid"\n4,3.2,1,62,2,3.57,2,4.0,"diploid"\n5,1.9,1,64,2,22.56,4,8.0,"tetraploid"\n6,4.8,0,69,1,6.14,3,7.0,"diploid"\n7,5.8,0,75,2,13.69,2,"","tetraploid"\n8,7.3,0,71,2,"",3,7.0,"aneuploid"\n9,3.7,1,73,2,11.77,3,6.0,"diploid"\n'

* QUOTING_NONNUMERIC为2。

现在，这不是完全你想要什么，因为没有引用索引列，我只想修改索引：

In [24]: df.index = df.index.astype(str) # unicode in python 3? In [25]: s = StringIO() In [26]: df.to_csv(s, quoting=2) In [27]: s.getvalue() Out[27]: '"","pgtime","pgstat","age","eet","g2","grade","gleason","ploidy"\n"1",6.1,0,64,2,10.26,2,4.0,"diploid"\n"2",9.4,0,62,1,"",3,8.0,"aneuploid"\n"3",5.2,1,59,2,9.99,3,7.0,"diploid"\n"4",3.2,1,62,2,3.57,2,4.0,"diploid"\n"5",1.9,1,64,2,22.56,4,8.0,"tetraploid"\n"6",4.8,0,69,1,6.14,3,7.0,"diploid"\n"7",5.8,0,75,2,13.69,2,"","tetraploid"\n"8",7.3,0,71,2,"",3,7.0,"aneuploid"\n"9",3.7,1,73,2,11.77,3,6.0,"diploid"\n'

根据需要。

Pandas，to_csv（）为特定格式

1 个答案: