Question

我有一个带有时间戳记的文本文件，它看起来像这样：

00:25
hold it miles lunch and remember I'm
00:30
working late tonight again man you're a
00:34
total slave to that business of yours
00:36
nobody's a slave to their own dream

我试图弄清楚如何将其导入到Pandas Dataframe中，如下所示：

[Time] [Text]
00:25  hold it miles lunch and remember I'm
00:30  working late tonight again man you're a
00:34  total slave to that business of yours
00:36  nobody's a slave to their own dream

我很尴尬地说我什至不知道从哪里开始...我知道并尝试过的所有方法都会产生这种结果：

  row1  00:25
  row2  hold it miles lunch and remember I'm
  row3  00:30
  row4  working late tonight again man you're a
  row5  00:34
  row6  total slave to that business of yours
  row7  00:36
  row8  nobody's a slave to their own dream

我发现了这个question，看起来似乎是相同的问题，但是我无法告诉您在创建数据框时如何应用它。

谢谢您的帮助！

Answer 1

这里是实现此目的的方法：

# Import the sample data
data='''00:25
hold it miles lunch and remember I'm
00:30
working late tonight again man you're a
00:34
total slave to that business of yours
00:36
nobody's a slave to their own dream'''

# Create a list containing every line
data = data.split('\n')

# Parse the data, assigning every other row to a different column
col1 = [data[i] for i in range(0,len(data),2)]
col2 = [data[i] for i in range(1,len(data),2)]

# Create the data frame
df = pd.DataFrame({'Time': col1, 'Text': col2})
print(df)

    Time                                     Text
0  00:25     hold it miles lunch and remember I'm
1  00:30  working late tonight again man you're a
2  00:34    total slave to that business of yours
3  00:36      nobody's a slave to their own dream

Answer 2

或者（如果text列中没有:）

m=df.col.str.contains(":")
df_new=pd.concat([df[m].reset_index(drop=True),df[~m].reset_index(drop=True)],axis=1)
df_new.columns=['Time','Text']
print(df_new)

    Time                                     Text
0  00:25     hold it miles lunch and remember I'm
1  00:30  working late tonight again man you're a
2  00:34    total slave to that business of yours
3  00:36      nobody's a slave to their own dream

Answer 3

另一种方法是拆分每一行，并将其他行分配给不同的列，例如“时间”和“文本”。最后，根据修改后的字典使其成为DataFrame。

import pandas as pd

# Read your files here 
files = ['text.txt'] #  you can add file or bunch of files
data = {}
for f in files:
  with open (f, "r") as myfile:
    all_lines = myfile.read().splitlines() # split by line
    # assign every alternative line to Time and Text index alternatively
    data['Time'], data['Text'] = all_lines[::2],  all_lines[1::2]

# create dataframe from the dictionary
df = pd.DataFrame(data)
print(df)

输出：

    Time                                     Text
0  00:25     hold it miles lunch and remember I'm
1  00:30  working late tonight again man you're a
2  00:34    total slave to that business of yours
3  00:36      nobody's a slave to their own dream

Python Pandas使用换行符从文件创建数据框？

3 个答案: