我正在阅读有关 read_html 的内容pandas 功能，因为我正在从网络中提取一些表格，所以当我这样做时:
import pandas as pd
url_mcc = 'link.com.html'
dfs = pd.read_html(url_mcc)
dfs
我得到以下列表:
[ Presentation \
0 0.4 mg/mL, 1 mL single-dose vial, package of 2...
1 1 mg/mL, 1 mL single-dose vial, package of 25 ...
Availability and Estimated Shortage Duration \
0 Available for NDC 00517-0401-25.
1 Available
Related Information \
0 American Regent is currently releasing the 0.4...
1 American Regent is currently releasing the 1mg...
Shortage Reason (per FDASIA)
0 Demand increase for the drug
1 Other ,
Presentation \
0 0.1 mg/mL; 10 mL Luer-Jet Prefilled Syringe (N...
Availability and Estimated Shortage Duration Related Information \
0 Product available NaN
Shortage Reason (per FDASIA)
0 Demand increase for the drug ,
Presentation \
0 0.1 mg/mL; 10 mL Ansyr syringe (NDC 0409-1630-10)
1 0.05 mg/mL; 5 mL Ansyr syringe (NDC 0409-9630-05)
2 0.1 mg/mL; 5 mL Lifeshield syringe (NDC 0409-4...
3 0.1 mg/mL; 10 mL Lifeshield syringe (NDC 0409-...
Availability and Estimated Shortage Duration \
0 Next delivery: Late October. Estimated recover...
1 Next delivery: TBD Estimated recovery: TBD
2 Available
3 Available
Related Information \
0 Please check with your wholesaler for availabl...
1 Please check with your wholesaler for availabl...
2 Shortage per Manufacturer: Available
3 Shortage per Manufacturer: Available
Shortage Reason (per FDASIA)
0 Other
1 Other
2 Other
3 Other ,
Presentation \
0 0.4 mg/mL, 20 mL vial (NDC 0641-6006-10)
Availability and Estimated Shortage Duration \
0 West-Ward has available inventory.
Related Information \
0 Additional lots are scheduled to be manufactur...
Shortage Reason (per FDASIA)
0 Demand increase for the drug ]
正如您所看到的，列表(或表格？)有重复的列:演示、可用性和预计短缺持续时间、相关信息、 短缺原因(根据 FDASIA)，因为该网站有 3 个具有相同列的不同表格。因此，我的问题是如何将所有不同的表格或列表扁平化或规范化为一个表格或列表，或多或少像这样:
[ Presentation \
0 0.4 mg/mL, 1 mL single-dose vial, package of 2...
1 1 mg/mL, 1 mL single-dose vial, package of 25 ...
2 1 mg/mL; 10 mL Luer-Jet Prefilled Syringe (N...
3 0.1 mg/mL; 10 mL Ansyr syringe (NDC 0409-1630-10)
4 0.05 mg/mL; 5 mL Ansyr syringe (NDC 0409-9630-05)
5 0.1 mg/mL; 5 mL Lifeshield syringe (NDC 0409-4...
6 0.1 mg/mL; 10 mL Lifeshield syringe (NDC 0409-...
Availability and Estimated Shortage Duration \
0 Available for NDC 00517-0401-25.
1 Available
2 Product available NaN
0 Next delivery: Late October. Estimated recover...
1 Next delivery: TBD Estimated recovery: TBD
2 Available
3 Available
0 0.4 mg/mL, 20 mL vial (NDC 0641-6006-10)
Availability and Estimated Shortage Duration \
0 West-Ward has available inventory.
Shortage Reason (per FDASIA)
0 Demand increase for the drug
Related Information \
0 American Regent is currently releasing the 0.4...
1 American Regent is currently releasing the 1mg...
0 Please check with your wholesaler for availabl...
1 Please check with your wholesaler for availabl...
2 Shortage per Manufacturer: Available
3 Shortage per Manufacturer: Available
0 Additional lots are scheduled to be manufactur...
Shortage Reason (per FDASIA)
0 Demand increase for the drug
1 Other ,
Shortage Reason (per FDASIA)
0 Demand increase for the drug ,
0 Other
1 Other
2 Other
3 Other ,
最佳答案
我认为你需要concat如果 dfs 是 DataFrames 列表:
df = pd.concat(dfs)
您还可以使用参数ignore_index=True来避免索引中出现重复:
df = pd.concat(dfs, ignore_index=True)
示例:
df1 = pd.DataFrame({'A':[1,2,3],
'B':[4,5,6],
'C':[7,8,9]})
#print (df1)
df2 = pd.DataFrame({'A':[3,4,6],
'B':[2,3,4],
'C':[3,6,0]})
#print (df2)
df3 = pd.DataFrame({'A':[4,7,9],
'B':[3,4,5],
'C':[5,1,9]})
#print (df3)
dfs = [df1,df2,df3]
print (dfs)
[ A B C
0 1 4 7
1 2 5 8
2 3 6 9, A B C
0 3 2 3
1 4 3 6
2 6 4 0, A B C
0 4 3 5
1 7 4 1
2 9 5 9]
df = pd.concat(dfs)
print (df)
A B C
0 1 4 7
1 2 5 8
2 3 6 9
0 3 2 3
1 4 3 6
2 6 4 0
0 4 3 5
1 7 4 1
2 9 5 9
df1 = pd.concat(dfs, ignore_index=True)
print (df1)
A B C
0 1 4 7
1 2 5 8
2 3 6 9
3 3 2 3
4 4 3 6
5 6 4 0
6 4 3 5
7 7 4 1
8 9 5 9
关于python - 如何从 pandas read_html 读取并平坦/规范化一系列表？，我们在Stack Overflow上找到一个类似的问题： https://stackoverflow.com/questions/40366105/