Emample:

text = [ ['This is the NLP TASKS ARTICLE written by Anjum**'] ,['IN this article I”ll be explaining various DATA-CLEANING techniques '], ['So stay tuned for FURther More && '],['Nah I dont think he goes to usf ; he lives around']]
df = pd.DataFrame({'text':text})

输出

一种简单的方法是使用StringIO。StringIO (python2)或io。StringIO (python3)并将其传递给pandas。read_csv函数。例句:

import sys
if sys.version_info[0] < 3: 
    from StringIO import StringIO
else:
    from io import StringIO

import pandas as pd

TESTDATA = StringIO("""col1;col2;col3
    1;4.4;99
    2;4.5;200
    3;4.7;65
    4;3.2;140
    """)

df = pd.read_csv(TESTDATA, sep=";")

Emample:

text = [ ['This is the NLP TASKS ARTICLE written by Anjum**'] ,['IN this article I”ll be explaining various DATA-CLEANING techniques '], ['So stay tuned for FURther More && '],['Nah I dont think he goes to usf ; he lives around']]
df = pd.DataFrame({'text':text})

输出

交互式工作的一个快速简单的解决方案是通过从剪贴板加载数据来复制并粘贴文本。

用鼠标选择字符串的内容:

在Python shell中使用read_clipboard()

>>> pd.read_clipboard()
  col1;col2;col3
0       1;4.4;99
1      2;4.5;200
2       3;4.7;65
3      4;3.2;140

使用适当的分隔符:

>>> pd.read_clipboard(sep=';')
   col1  col2  col3
0     1   4.4    99
1     2   4.5   200
2     3   4.7    65
3     4   3.2   140

>>> df = pd.read_clipboard(sep=';') # save to dataframe

在一行中，但首先导入io

import pandas as pd
import io   

TESTDATA="""col1;col2;col3
1;4.4;99
2;4.5;200
3;4.7;65
4;3.2;140
"""

df = pd.read_csv(io.StringIO(TESTDATA), sep=";")
print(df)

对象:获取字符串make dataframe。

解决方案

def str2frame(estr, sep = ',', lineterm = '\n', set_header = True):
    dat = [x.split(sep) for x in estr.split(lineterm)][1:-1]
    df = pd.DataFrame(dat)
    if set_header:
        df = df.T.set_index(0, drop = True).T # flip, set ix, flip back
    return df

例子

estr = """
sym,date,strike,genus
APPLE,20MAY20,50.0,Malus
ORANGE,22JUL20,50.0,Rutaceae
"""

df = str2frame(estr)

print(df)
0     sym     date strike     genus
1   APPLE  20MAY20   50.0     Malus
2  ORANGE  22JUL20   50.0  Rutaceae