我有一个这样的数据框:
element_index
这些是我之前关于以这种格式导入数据框的问题。
我首先创建了一个列表:
Item Quantity Price Photo1 Photo2 Photo3 Photo4
A 2 30 A1.jpg A2.jpg
B 4 10 B1.jpg B2.jpg B3.jpg B4.jpg
C 5 15 C1.jpg
我从第一个问题开始尝试:
df1 = df.reindex(['Item','Quantity','Price','Photo1','Photo2','Photo3','Photo4','I','Q','P','PH',] axis=1)
df1['I'] = df1['I'].fillna['I']
df1['Q'] = df1['Q'].fillna['Q']
df1['P'] = df1['P'].fillna['P']
df1['PH'] = df1['PH'].fillna['PH']
vals = [['I','Item'],['Q','Quantity'],['P','Price']]
列表返回
photo_df = df1.fillna('').filter(like='Photo')
vals = [y for x in photo_df.to_numpy()
for y in vals[:3] + [['PH',z] for z in x[x!='']] ]
我希望列表如下:
vals = [['I','Item'],['Q','Quantity'],['P','Price'],['PH','A1.jpg'],['PH','A2.jpg'],
['I','Item'],['Q','Quantity'],['P','Price'],['PH','B1.jpg'],['PH','B2.jpg'],['PH','B3.jpg'],['PH','B4.jpg'],
['I','Item'],['Q','Quantity'],['P','Price'],['PH','C1.jpg']]
我想在列表中保留标题名称而不是数据,但应该以问题中的格式迭代数据: How to split datas from columns and add to a list from a dataframe, also repeat the list elements for a single row? (Pandas)
答案 0 :(得分:3)
您可以像这样在创建 photo_df
的地方做一个小改动:
photo_df = df1.filter(like='Photo')
photo_df = photo_df.transform(lambda x: np.where(x.isnull(), x, x.name))
photo_df = photo_df.fillna('')
第二行只是将非空值替换为其列名。
输出:
[['I', 'Item'], ['Q', 'Quantity'], ['P', 'Price'], ['PH', 'Photo1'], ['PH', 'Photo2'],
['I', 'Item'], ['Q', 'Quantity'], ['P', 'Price'], ['PH', 'Photo1'], ['PH', 'Photo2'],
['PH', 'Photo3'], ['PH', 'Photo4'], ['I', 'Item'], ['Q', 'Quantity'], ['P', 'Price'], ['PH', 'Photo1']]
答案 1 :(得分:2)
想法是过滤列名称而不是列表理解中的值 - 将 x[x!='']
更改为 photo_df.columns[x!='']
:
vals = [y for x in photo_df.to_numpy()
for y in vals[:3] + [['PH',z]
for z in photo_df.columns[x!='']]]
print (vals)
[['I', 'Item'], ['Q', 'Quantity'], ['P', 'Price'], ['PH', 'Photo1'], ['PH', 'Photo2'],
['I', 'Item'], ['Q', 'Quantity'], ['P', 'Price'], ['PH', 'Photo1'], ['PH', 'Photo2'], ['PH', 'Photo3'], ['PH', 'Photo4'],
['I', 'Item'], ['Q', 'Quantity'], ['P', 'Price'], ['PH', 'Photo1']]