Python 从熊猫数据框中删除标题列
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Removing header column from pandas dataframe
提问by user308827
I have the foll. dataframe:
我有一个愚蠢的。数据框：
df
df
A B
0 23 12
1 21 44
2 98 21
How do I remove the column names Aand Bfrom this dataframe? One way might be to write it into a csv file and then read it in specifying header=None. is there a way to do that without writing out to csv and re-reading?
如何删除列名A，并B从该数据帧？一种方法可能是将其写入 csv 文件，然后在指定 header=None 时读取它。有没有办法在不写出 csv 并重新阅读的情况下做到这一点？
回答by jezrael
I think you cant remove column names, only reset them by rangewith shape:
我认为你不能删除列名，只能通过重新设置range有shape：
print df.shape[1]
2
print range(df.shape[1])
[0, 1]
df.columns = range(df.shape[1])
print df
0 1
0 23 12
1 21 44
2 98 21
This is same as using to_csvand read_csv:
print df.to_csv(header=None,index=False)
23,12
21,44
98,21
print pd.read_csv(io.StringIO(u""+df.to_csv(header=None,index=False)), header=None)
0 1
0 23 12
1 21 44
2 98 21
Next solution with skiprows:
下一个解决方案skiprows：
print df.to_csv(index=False)
A,B
23,12
21,44
98,21
print pd.read_csv(io.StringIO(u""+df.to_csv(index=False)), header=None, skiprows=1)
0 1
0 23 12
1 21 44
2 98 21
回答by Max
How to get rid of a header(first row) and an index(first column).
如何摆脱标题（第一行）和索引（第一列）。
To write to CSV file:
写入 CSV 文件：
df = pandas.DataFrame(your_array)
df.to_csv('your_array.csv', header=False, index=False)
To read from CSV file:
从 CSV 文件中读取：
df = pandas.read_csv('your_array.csv')
a = df.values
If you want to read a CSV file that doesn't contain a header, pass additional parameter header:
如果要读取不包含标题的 CSV 文件，请传递附加参数header：
df = pandas.read_csv('your_array.csv', header=None)
