Python:从列表创建 pandas 数据框 [英] Python: create a pandas data frame from a list

问题描述

我正在使用以下代码从列表创建数据框:

I am using the following code to create a data frame from a list:

test_list = ['a','b','c','d']
df_test = pd.DataFrame.from_records(test_list, columns=['my_letters'])
df_test

上面的代码工作正常.然后我尝试了另一种列表的相同方法:

The above code works fine. Then I tried the same approach for another list:

import pandas as pd
q_list = ['112354401', '116115526', '114909312', '122425491', '131957025', '111373473']
df1 = pd.DataFrame.from_records(q_list, columns=['q_data'])
df1

但这一次给了我以下错误:

But it gave me the following errors this time:

---------------------------------------------------------------------------
AssertionError                            Traceback (most recent call last)
<ipython-input-24-99e7b8e32a52> in <module>()
      1 import pandas as pd
      2 q_list = ['112354401', '116115526', '114909312', '122425491', '131957025', '111373473']
----> 3 df1 = pd.DataFrame.from_records(q_list, columns=['q_data'])
      4 df1

/usr/local/lib/python3.4/dist-packages/pandas/core/frame.py in from_records(cls, data, index, exclude, columns, coerce_float, nrows)
   1021         else:
   1022             arrays, arr_columns = _to_arrays(data, columns,
-> 1023                                              coerce_float=coerce_float)
   1024 
   1025             arr_columns = _ensure_index(arr_columns)

/usr/local/lib/python3.4/dist-packages/pandas/core/frame.py in _to_arrays(data, columns, coerce_float, dtype)
   5550         data = lmap(tuple, data)
   5551         return _list_to_arrays(data, columns, coerce_float=coerce_float,
-> 5552                                dtype=dtype)
   5553 
   5554 

/usr/local/lib/python3.4/dist-packages/pandas/core/frame.py in _list_to_arrays(data, columns, coerce_float, dtype)
   5607         content = list(lib.to_object_array(data).T)
   5608     return _convert_object_array(content, columns, dtype=dtype,
-> 5609                                  coerce_float=coerce_float)
   5610 
   5611 

/usr/local/lib/python3.4/dist-packages/pandas/core/frame.py in _convert_object_array(content, columns, coerce_float, dtype)
   5666             # caller's responsibility to check for this...
   5667             raise AssertionError('%d columns passed, passed data had %s '
-> 5668                                  'columns' % (len(columns), len(content)))
   5669 
   5670     # provide soft conversion of object dtypes

AssertionError: 1 columns passed, passed data had 9 columns

为什么相同的方法适用于一个列表却不适用于另一个列表?知道这里可能有什么问题吗?非常感谢！

Why would the same approach work for one list but not another? Any idea what might be wrong here? Thanks a lot!

推荐答案

DataFrame.from_records将字符串视为字符列表.因此它需要与字符串长度一样多的列.

DataFrame.from_records treats string as a character list. so it needs as many columns as length of string.

您可以简单地使用DataFrame构造函数.

You could simply use DataFrame constructor.

In [3]: pd.DataFrame(q_list, columns=['q_data'])
Out[3]:
      q_data
0  112354401
1  116115526
2  114909312
3  122425491
4  131957025
5  111373473

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