pandas 你能阻止 df.append() 的自动字母顺序吗？
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Can you prevent automatic alphabetical order of df.append()?
提问by Alexis Perez
I am trying to append data to a log where the order of columns isn't in alphabetical order but makes logical sense, ex.
我试图将数据附加到日志中，其中列的顺序不是按字母顺序排列，但具有逻辑意义，例如。
Org_Goals_1 Calc_Goals_1 Diff_Goals_1 Org_Goals_2 Calc_Goals_2 Diff_Goals_2
I am running through several calculations based on different variables and logging the results through appending a dictionary of the values after each run. Is there a way to prevent the df.append() function to order the columns alphabetically?
我正在运行基于不同变量的多个计算，并通过在每次运行后附加值字典来记录结果。有没有办法阻止 df.append() 函数按字母顺序排列列？
采纳答案by EdChum
Seems you have to reorder the columns after the append operation:
似乎您必须在追加操作后对列重新排序：
In [25]:
# assign the appended dfs to merged
merged = df1.append(df2)
# create a list of the columns in the order you desire
cols = list(df1) + list(df2)
# assign directly
merged.columns = cols
# column order is now as desired
merged.columns
Out[25]:
Index(['Org_Goals_1', 'Calc_Goals_1', 'Diff_Goals_1', 'Org_Goals_2', 'Calc_Goals_2', 'Diff_Goals_2'], dtype='object')
example:
例子：
In [26]:
df1 = pd.DataFrame(columns=['Org_Goals_1','Calc_Goals_1','Diff_Goals_1'], data = randn(5,3))
df2 = pd.DataFrame(columns=['Org_Goals_2','Calc_Goals_2','Diff_Goals_2'], data=randn(5,3))
merged = df1.append(df2)
cols = list(df1) + list(df2)
merged.columns = cols
merged
Out[26]:
Org_Goals_1 Calc_Goals_1 Diff_Goals_1 Org_Goals_2 Calc_Goals_2 \
0 0.028935 NaN -0.687143 NaN 1.528579
1 0.943432 NaN -2.055357 NaN -0.720132
2 0.035234 NaN 0.020756 NaN 1.556319
3 1.447863 NaN 0.847496 NaN -1.458852
4 0.132337 NaN -0.255578 NaN -0.222660
0 NaN 0.131085 NaN 0.850022 NaN
1 NaN -1.942110 NaN 0.672965 NaN
2 NaN 0.944052 NaN 1.274509 NaN
3 NaN -1.796448 NaN 0.130338 NaN
4 NaN 0.961545 NaN -0.741825 NaN
Diff_Goals_2
0 NaN
1 NaN
2 NaN
3 NaN
4 NaN
0 0.727619
1 0.022209
2 -0.350757
3 1.116637
4 1.947526
The same alpha sorting of the columns happens with concat also so it looks like you have to reorder after appending.
列的相同 alpha 排序也发生在 concat 中，因此看起来您必须在追加后重新排序。
EDIT
编辑
An alternative is to use join:
另一种方法是使用join：
In [32]:
df1.join(df2)
Out[32]:
Org_Goals_1 Calc_Goals_1 Diff_Goals_1 Org_Goals_2 Calc_Goals_2 \
0 0.163745 1.608398 0.876040 0.651063 0.371263
1 -1.762973 -0.471050 -0.206376 1.323191 0.623045
2 0.166269 1.021835 -0.119982 1.005159 -0.831738
3 -0.400197 0.567782 -1.581803 0.417112 0.188023
4 -1.443269 -0.001080 0.804195 0.480510 -0.660761
Diff_Goals_2
0 -2.723280
1 2.463258
2 0.147251
3 2.328377
4 -0.248114
回答by Alexis Perez
Actually, I found "advanced indexing" to work quite well
实际上，我发现“高级索引”效果很好
df2=df.ix[:,'order of columns']
回答by Maarten Klop
As I see it, the order is lost, but when appending, the original data should have the correct order. To maintain that, assuming Dataframe 'alldata' and dataframe to be appended data 'newdata', appending and keeping column order as in 'alldata' would be:
在我看来，顺序丢失了，但是在追加时，原始数据应该具有正确的顺序。为了保持这一点，假设 Dataframe 'alldata' 和 dataframe 被附加数据 'newdata'，在 'alldata' 中附加和保持列顺序将是：
alldata.append(newdata)[list(alldata)]
(I encountered this problem with named date fields, where 'Month' would be sorted between 'Minute' and 'Second')
（我在命名日期字段中遇到了这个问题，其中“月”将在“分钟”和“秒”之间排序）
