I have a simple 2 column csv file called st1.csv:
我有一个名为st1.csv的简单2列csv文件:
GRID St1
1457 614
1458 657
1459 679
1460 732
1461 754
1462 811
1463 748
However, when I try to read the csv file, the first column is not loaded:
但是,当我尝试读取csv文件时,未加载第一列:
a = pandas.DataFrame.from_csv('st1.csv')
a.columns
outputs:
输出:
Index([u'ST1'], dtype=object)
Why is the first column not being read?
为什么没有读取第一列?
2 个解决方案
#1
36
Judging by your data it looks like the delimiter you're using is a .
根据您的数据判断,您使用的分隔符看起来像是。
Try the following:
请尝试以下方法:
a = pandas.DataFrame.from_csv('st1.csv', sep=' ')
The other issue is that it's assuming your first column is an index, which we can also disable:
另一个问题是它假设你的第一列是一个索引,我们也可以禁用它:
a = pandas.DataFrame.from_csv('st1.csv', index_col=None)
#2
6
Based on documentation which compares read_csv
and from_csv
, it shows that it is possible to put index_col = None
. I tried the below and it worked:
根据比较read_csv和from_csv的文档,它显示可以放入index_col = None。我尝试了下面的工作:
DataFrame.from_csv('st1.csv', index_col=None);
This assumes that the data is comma-separated.
这假定数据以逗号分隔。
Please check the below link
请检查以下链接
http://pandas.pydata.org/pandas-docs/stable/generated/pandas.DataFrame.from_csv.html
http://pandas.pydata.org/pandas-docs/stable/generated/pandas.DataFrame.from_csv.html
#1
36
Judging by your data it looks like the delimiter you're using is a .
根据您的数据判断,您使用的分隔符看起来像是。
Try the following:
请尝试以下方法:
a = pandas.DataFrame.from_csv('st1.csv', sep=' ')
The other issue is that it's assuming your first column is an index, which we can also disable:
另一个问题是它假设你的第一列是一个索引,我们也可以禁用它:
a = pandas.DataFrame.from_csv('st1.csv', index_col=None)
#2
6
Based on documentation which compares read_csv
and from_csv
, it shows that it is possible to put index_col = None
. I tried the below and it worked:
根据比较read_csv和from_csv的文档,它显示可以放入index_col = None。我尝试了下面的工作:
DataFrame.from_csv('st1.csv', index_col=None);
This assumes that the data is comma-separated.
这假定数据以逗号分隔。
Please check the below link
请检查以下链接
http://pandas.pydata.org/pandas-docs/stable/generated/pandas.DataFrame.from_csv.html
http://pandas.pydata.org/pandas-docs/stable/generated/pandas.DataFrame.from_csv.html