在 Pandas to_csv 方法中保留列顺序
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Preserving column order in the pandas to_csv method
提问by Thej Kiran
The to_csv method of pandas does not preserve the order of columns. It chooses to alphabetically arrange the columns in CSV. This is a bug and has been reported and is supposed to be corrected in version 0.11.0. I have 0.18.0.
pandas 的 to_csv 方法不保留列的顺序。它选择按字母顺序排列 CSV 中的列。这是一个错误，已被报告，应该在 0.11.0 版中更正。我有 0.18.0。
import pandas as pd
df = pd.DataFrame({'V_pod_error' : [a],
'V_pod_used' : [b],
'U_sol_type' : [c]
...
... and so on upto 50 columns }
pd.to_csv(df)
Excel order:
Excel订单：
0 U_sol type V_pod_error V_pod_used ...
1
What I want is order in the dictionary:
我想要的是字典中的顺序：
0 V_pod_error V_pod_used U_sol type ...
1
I have a huge number of columns and names. I cannot do it manually or write out the column order. There has been the exact same question in 2013 here. And it doesnt look like there is an update! I would like to ask the community to help me out! This is really problematic.
我有大量的列和名称。我无法手动完成或写出列顺序。2013 年这里有完全相同的问题。而且看起来好像没有更新！我想请社区帮助我！这确实有问题。
采纳答案by Saranya Krishnamurthy
Try the following solution. Even I faced the same issue. I solved it as follows:
尝试以下解决方案。甚至我也面临同样的问题。我是这样解决的：
import pandas as pd
df = pd.DataFrame({'V_pod_error' : [a],
'V_pod_used' : [b],
'U_sol_type' : [c]
...
... and so on upto 50 columns }
column_order = ['V_pod_error', 'V_pod_used', 'U_sol_type',.....# upto 50 column names]
df[column_order].to_csv(file_name)
回答by jezrael
I think problem is in DataFrameconstructor, because you need add parameter columnsfor custom ordering of columns. If you dont set parameter columns, columns are ordered alphanumerical.
我认为问题出在DataFrame构造函数中，因为您需要columns为列的自定义排序添加参数。如果不设置参数列，则列按字母数字顺序排列。
import pandas as pd
df = pd.DataFrame({'V_pod_error' : [0,2],
'V_pod_used' : [6,4],
'U_sol_type' : [7,8]})
print df
U_sol_type V_pod_error V_pod_used
0 7 0 6
1 8 2 4
print df.to_csv()
,U_sol_type,V_pod_error,V_pod_used
0,7,0,6
1,8,2,4
df1 = pd.DataFrame({'V_pod_error' : [0,2],
'V_pod_used' : [6,4],
'U_sol_type' : [7,8]},
columns=['V_pod_error','V_pod_used','U_sol_type'])
print df1
V_pod_error V_pod_used U_sol_type
0 0 6 7
1 2 4 8
print df1.to_csv()
,V_pod_error,V_pod_used,U_sol_type
0,0,6,7
1,2,4,8
EDIT:
编辑：
Another solution is set order of column by subset before write to_csv(thanks Mathias711):
另一种解决方案是在写入之前按子集设置列顺序to_csv（感谢Mathias711）：
import pandas as pd
df = pd.DataFrame({'V_pod_error' : [0,2],
'V_pod_used' : [6,4],
'U_sol_type' : [7,8]})
print df
U_sol_type V_pod_error V_pod_used
0 7 0 6
1 8 2 4
df = df[['V_pod_error','V_pod_used','U_sol_type']]
print df
V_pod_error V_pod_used U_sol_type
0 0 6 7
1 2 4 8
EDIT1: Maybe help first convert dictto OrderedDictand then create DataFrame:
EDIT1：也许有助于首先转换dict为OrderedDict然后创建DataFrame：
import collections
import pandas as pd
d = {'V_pod_error' : [0,2],'V_pod_used' : [6,4], 'U_sol_type' : [7,8]}
print d
{'V_pod_error': [0, 2], 'V_pod_used': [6, 4], 'U_sol_type': [7, 8]}
print pd.DataFrame(d)
U_sol_type V_pod_error V_pod_used
0 7 0 6
1 8 2 4
d1 = collections.OrderedDict(d)
print d1
OrderedDict([('V_pod_error', [0, 2]), ('V_pod_used', [6, 4]), ('U_sol_type', [7, 8])])
print pd.DataFrame(d1)
V_pod_error V_pod_used U_sol_type
0 0 6 7
1 2 4 8
回答by Biranchi
Try with:
尝试：
df.to_csv(file_name, sep=',', encoding='utf-8', header=True, columns=["Col1","Col2","Col3","Col4"])
http://pandas.pydata.org/pandas-docs/stable/generated/pandas.DataFrame.to_csv.html
http://pandas.pydata.org/pandas-docs/stable/generated/pandas.DataFrame.to_csv.html
