Python 如何将web URL.txt数据转换为Dataframa
我试图从中下载数据并将其放入单个数据帧中 我一直在检索正确的数据列名,我想找到正确的表列标题,下面的代码不起作用Python 如何将web URL.txt数据转换为Dataframa,python,python-3.x,pandas,dataframe,Python,Python 3.x,Pandas,Dataframe,我试图从中下载数据并将其放入单个数据帧中 我一直在检索正确的数据列名,我想找到正确的表列标题,下面的代码不起作用 Header = pd.read_csv(io.StringIO(URL_Data.decode('utf-8')), delimiter='\t', skiprows=4, nrows=4) 数据提取: Data = pd.read_csv(io.StringIO(URL_Data.decode('utf-8')), skiprows=9, delim_whitespace=Tr
Header = pd.read_csv(io.StringIO(URL_Data.decode('utf-8')), delimiter='\t', skiprows=4, nrows=4)
数据提取:
Data = pd.read_csv(io.StringIO(URL_Data.decode('utf-8')), skiprows=9, delim_whitespace=True, header=Header, error_bad_lines=False)
Data.to_csv(r"D:\Sunil_Work\psnl\python\DataFile.csv")
与和连接一起使用
:
url = 'https://www.federalreserve.gov/paymentsystems/files/check_commcheckcolqtr.txt '
Indicator_Name = pd.read_csv(url, nrows=1, header=None)
Header = pd.read_fwf(url, skiprows=4, header=None, error_bad_lines=False, nrows=5)
Header = Header.agg(lambda x: ' '.join(x.dropna()))
print (Header)
0 Quarter
1 Volume (millions of items)
2 Volume percent change
3 Value (billions of dollars)
4 Value percent change
5 Average daily volume (millions of items)
6 Average daily value (billions of dollars)
7 Average value per check (dollars)
dtype: object
Data = pd.read_csv(url, skiprows=9, delim_whitespace=True, names=Header, error_bad_lines=False)
问题是什么?你有什么错误吗?@Rakesh,头球没有正确传来。我想保留适当的标题,但在源代码中,标题被拆分为多行。
print (Data.head(3))
Quarter Volume (millions of items) Volume percent change \
0 2018:Q4 1,169 1.9
1 2018:Q3 1,147 -5.4
2 2018:Q2 1,212 0.1
Value (billions of dollars) Value percent change \
0 2,072 0.0
1 2,072 -8.9
2 2,274 10.0
Average daily volume (millions of items) \
0 18.9
1 18.2
2 18.9
Average daily value (billions of dollars) Average value per check (dollars)
0 33.4 1,772
1 32.9 1,805
2 35.5 1,875