Python: create a pandas data frame from a list

Question

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 

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 

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 

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

Answer 1

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

You could simply use the 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