我使用以下代码从列表创建数据框:
test_list = ['a','b','c','d']
df_test = pd.DataFrame.from_records(test_list, columns=['my_letters'])
df_test
上面的代码运行良好。然后我对另一个列表尝试了同样的方法:
import pandas as pd
q_list = ['112354401', '116115526', '114909312', '122425491', '131957025', '111373473']
df1 = pd.DataFrame.from_records(q_list, columns=['q_data'])
df1
但这一次它给了我以下错误:
---------------------------------------------------------------------------
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
为什么同样的方法只适用于一个列表,而不适用于另一个列表?知道这里可能出了什么问题吗?非常感谢!
5条答案
按热度按时间ne5o7dgx1#
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。您可以简单地使用the
DataFrame
constructor。2cmtqfgy2#
5gfr0r5j3#
如果你想从多个列表中创建一个DataFrame,你可以简单地压缩列表。这将返回一个“zip”对象。所以你将转换回一个列表。
sc4hvdpw4#
你也可以借助numpy。
pvabu6sv5#
只使用
concat
方法