python - 如何通过指定关键字对 pandas 数据框中的列名称进行排序

Question

以 list 或 dict 格式指定任意关键字，如下
是否可以对数据框中的列进行排序？

df = pd.DataFrame ({  
    "col_cc_7": [0, 0, 0],  
    "col_aa_7": [1, 1, 1],  
    "col_bb_7": [2, 2, 2]})

# before  
col_cc_7, col_aa_7, col_bb_7  
0,        1,        2  
0,        1,        2  
0,        1,        2  

# sort  
custom_sort_key = ["aa", "bb", "cc"]  
# ... sort codes ...  

# after  
col_aa_7, col_bb_7, col_cc_7  
1, 2, 0  
1, 2, 0  
1, 2, 0  

Answer 1

我们可以按中间值进行拆分并创建列的字典，然后在将其分配回之前应用排序。我添加了一些不属于您排序的额外列，以显示它们会发生什么。

df = pd.DataFrame ({  
    "col_cc_7": [0, 0, 0],  
    "col_aa_7": [1, 1, 1],  
    "col_bb_7": [2, 2, 2],
    "col_ee_7": [2, 2, 2],
    "col_dd_7": [2, 2, 2]})

custom_sort_key = ["bb", "cc", "aa"]  

col_dict = dict(zip(df.columns,[x.split('_')[1] for x in df.columns.tolist()]))

#{'col_cc_7': 'cc',
# 'col_aa_7': 'aa',
# 'col_bb_7': 'bb',
# 'col_ee_7': 'ee',
# 'col_dd_7': 'dd'}
d = {v:k for k,v in enumerate(custom_sort_key)}


# this will only work on python 3.6 +
new_cols = dict(sorted(col_dict.items(), key=lambda x: d.get(x[1], float('inf'))))

df[new_cols.keys()]
       col_bb_7  col_cc_7  col_aa_7  col_ee_7  col_dd_7
0         2         0         1         2         2
1         2         0         1         2         2
2         2         0         1         2         2