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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!
271
Pandas series can be converted to a list using tolist() or type casting method. There can be situations when you want to perform operations on a list instead of a pandas object. In such cases, you can store the DataFrame columns in a list and perform the required operations.
Use pd. DataFrame. from_dict() to transform a list of dictionaries to pandas DatFrame. This function is used to construct DataFrame from dict of array-like or dicts.
When we create dataframe from a list of dictionaries, matching keys will be the columns and corresponding values will be the rows of the dataframe. If there is no matching values and columns in the dictionary, then NaN value will be inserted in the resulted dataframe. For example, Python3.
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 If you love us? You can donate to us via Paypal or buy me a coffee so we can maintain and grow! Thank you!
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