pandas :创建数据框时不按字母顺序自动排序列名 [英] Pandas: create dataframe without auto ordering column names alphabetically

问题描述

我正在创建一个初始的熊猫数据框，以存储从其他代码生成的结果:例如

I am creating an initial pandas dataframe to store results generated from other codes: e.g.

result = pd.DataFrame({'date': datelist, 'total': [0]*len(datelist), 
                       'TT': [0]*len(datelist)})

带有datelist的预定义列表.然后其他代码将为每个date输出total和TT的一些数字，这些数字将存储在result数据框中.

with datelist a predefined list. Then other codes will output some number for total and TT for each date, which I will store in the result dataframe.

所以我希望第一列是date，第二列是total和第三列TT.但是，熊猫在创建时会自动按字母顺序将其重新排序为TT，date，total.虽然我之后可以手动重新排序，但我想知道是否有一种更简单的方法可以一步完成.

So I want the first column to be date, second total and third TT. However, pandas will automatically reorder it alphabetically to TT, date, total at creation. While I can manually reorder this again afterwards, I wonder if there is an easier way to achieve this in one step.

我认为我也可以做到

result = pd.DataFrame(np.transpose([datelist, [0]*l, [0]*l]),
                      columns = ['date', 'total', 'TT'])

但是它看起来也很乏味.还有其他建议吗?

but it somehow also looks tedious. Any other suggestions?

推荐答案

您可以将列(正确排序)的列表作为参数传递给构造函数，或使用OrderedDict:

You can pass the (correctly ordered) list of column as parameter to the constructor or use an OrderedDict:

# option 1:
result = pd.DataFrame({'date': datelist, 'total': [0]*len(datelist), 
                   'TT': [0]*len(datelist)}, columns=['date', 'total', 'TT'])

# option 2:
od = collections.OrderedDict()
od['date'] = datelist
od['total'] = [0]*len(datelist)
od['TT'] = [0]*len(datelist)
result = pd.DataFrame(od)

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