简体   繁体   English

将CSV中的数据重塑为多列

[英]Reshaping data in CSV to multiple columns

0   19   1   19   2   19  3   19

How can i change this above csv data in python to - 我如何在python中将以上csv数据更改为-

0   19
1   19
2   19
3   19

now i need help with reshaping my dataset which looks like this - 现在我需要重塑数据集的帮助,如下所示-

0   100   1   100   2   100  3   100  4   100  5   100     
6   200   7   200   8   200  9   200  0   200  1   200  
.....    

I want to reshape my dataset in the following format - 我想以以下格式重塑数据集-

0 100
1 100
2 100
3 100
4 100
5 100
..
6 200
7 200
8 200
9 200
0 200
1 200
...

You don't really need pandas. 您真的不需要熊猫。 You can do this with np.loadtxt followed by a reshape . 您可以使用np.loadtxt进行此操作,然后进行reshape

import io

# replace this with your filename 
buf = io.StringIO('''0   19   1   19   2   19  3   19''')   # buf = 'file.txt'

arr = np.loadtxt(buf).reshape(-1, 2)    
arr

array([[  0.,  19.],
       [  1.,  19.],
       [  2.,  19.],
       [  3.,  19.]])

Note that if you have a different delimiter (example, comma), then you can specify it by passing a delimiter argument like so: np.loadtxt(buf, delimiter=',') . 请注意,如果您使用其他定界符(例如,逗号),则可以通过传递delimiter参数来指定它,例如: np.loadtxt(buf, delimiter=',')

Now, save to CSV using savetxt - 现在,使用savetxt保存为savetxt

np.savetxt('file.csv', arr, delimiter=',')

Later, when reading your CSV using pandas , use - 稍后,当使用pandas读取CSV时,请使用-

df = pd.read_csv(index_col=[0], header=None, names=['A', 'B'])
from io import StringIO

txt = """0   19   1   19   2   19  3   19
"""

df = pd.read_csv(StringIO(txt),header=None,sep=' ')
df=df.dropna(1)

pd.DataFrame(df.T[0].values.reshape(df.shape[1]//2,2))
Out[77]: 
   0   1
0  0  19
1  1  19
2  2  19
3  3  19

声明:本站的技术帖子网页,遵循CC BY-SA 4.0协议,如果您需要转载,请注明本站网址或者原文地址。任何问题请咨询:yoyou2525@163.com.

 
粤ICP备18138465号  © 2020-2024 STACKOOM.COM