Question

我正在尝试清理Excel文件以进行进一步的研究。我有问题，我想合并第一行和第二行。我现在的代码：

xl = pd.ExcelFile("nanonose.xls")
df = xl.parse("Sheet1")
df = df.drop('Unnamed: 2', axis=1)
## Tried this line but no luck
##print(df.head().combine_first(df.iloc[[0]]))

这个输出是：

      Nanonose     Unnamed: 1     A     B    C          D          E  \
0  Sample type  Concentration   NaN   NaN  NaN        NaN        NaN   
1        Water           9200  95.5  21.0  6.0  11.942308  64.134615   
2        Water           9200  94.5  17.0  5.0   5.484615  63.205769   
3        Water           9200  92.0  16.0  3.0  11.057692  62.586538   
4        Water           4600  53.0   7.5  2.5   3.538462  35.163462   

           F         G         H  
0        NaN       NaN       NaN  
1  21.498560  5.567840  1.174135  
2  19.658560  4.968000  1.883444  
3  19.813120  5.192480  0.564835  
4   6.876207  1.641724  0.144654

所以，我的目标是合并第一行和第二行得到：样本类型|浓度| A | B | C | D | E | F | G | ħ

有人可以帮我合并这两行吗？

Answer 1

我认为你需要numpy.concatenate，类似的原则如cᴏʟᴅsᴘᴇᴇᴅ回答：

df.columns = np.concatenate([df.iloc[0, :2], df.columns[2:]])
df = df.iloc[1:].reset_index(drop=True)
print (df)
  Sample type Concentration     A     B    C          D          E          F  \
0       Water          9200  95.5  21.0  6.0  11.942308  64.134615  21.498560   
1       Water          9200  94.5  17.0  5.0   5.484615  63.205769  19.658560   
2       Water          9200  92.0  16.0  3.0  11.057692  62.586538  19.813120   
3       Water          4600  53.0   7.5  2.5   3.538462  35.163462   6.876207   

          G         H  
0  5.567840  1.174135  
1  4.968000  1.883444  
2  5.192480  0.564835  
3  1.641724  0.144654

Answer 2

只需重新分配 df.columns 。

df.columns = np.append(df.iloc[0, :2], df.columns[2:])

或者，

df.columns = df.iloc[0, :2].tolist() + (df.columns[2:]).tolist()

接下来，跳过第一行。

df = df.iloc[1:].reset_index(drop=True) 
df
  Sample type Concentration     A     B    C          D          E          F  \
0       Water          9200  95.5  21.0  6.0  11.942308  64.134615  21.498560   
1       Water          9200  94.5  17.0  5.0   5.484615  63.205769  19.658560   
2       Water          9200  92.0  16.0  3.0  11.057692  62.586538  19.813120   
3       Water          4600  53.0   7.5  2.5   3.538462  35.163462   6.876207   

          G         H  
0  5.567840  1.174135  
1  4.968000  1.883444  
2  5.192480  0.564835  
3  1.641724  0.144654

如果您希望最终输出为0索引，则

reset_index 是可选的。

Answer 3

获取第二行标题中的所有列，然后获取第一行标题中的所有列。组合它们以构成“所有列名称标头”列表。现在通过将header作为header [0,1]，用excel创建df。现在，将其标题替换为您先前创建的所有列名称标题。

import pandas as pd

#reading Second header row columns
df1 = pd.read_excel('nanonose.xls', header=[1] , index = False)
cols1 = df1.columns.tolist()
SecondRowColumns = []
for c in cols1:
    if ("Unnamed" or "NaN" not in c):
        SecondRowColumns.append(c)     

#reading First header row columns
df2 = pd.read_excel('nanonose.xls', header=[0] , index = False)
cols2 = df2.columns.tolist()
FirstRowColumns = []
for c in cols2:
    if ("Unnamed" or "Nanonose" not in c):
        FirstRowColumns.append(c)       

AllColumn = []
AllColumn = SecondRowColumns+ FirstRowColumns



df = pd.read_excel('nanonose.xls', header=[0,1] , index=False)
df.columns = AllColumn
print(df)

将第一行与数据框

3 个答案: