How to concatenate multiple data frames with long index without error?

Question

I have a directory ".../dados" in which have multiple subdirectories whose names are a serial number plus some useless information - e.g. "17448_2017_Jul_2017_Oct", where the first number on it is the serial number. Inside each subdirectory, I have four ".txt" files whose lines/rows have the information of date and time, and an attribute of a certain type, say humidity, all named the same way in each subdirectory - e.g. "2019-01-29 03:11:26 54.7".

I want to concatenate all of them in order to generate a dataset with date index.

path = "/.../dados/"

df = pd.DataFrame()

for fld in os.listdir(path):
    subfld = path + fld
    if os.path.isdir(subfld):
        aux = pd.DataFrame()
        sn = fld.split('_')[0]
        for file in os.listdir(subfld):
            filepath = os.path.join(subfld, file)
            if os.path.isfile(filepath):
                new_col = pd.read_fwf(filepath, colspecs=[(0, 19), (20, -1)], skiprows=8, names=[file.split('_')[2][:-4]], parse_dates=[0], nrows=9999999)
                aux = pd.concat([aux, new_col], axis=1,  sort=False)
        aux['Machine'] = sn
        df = df.append(aux)

This is a print of df.head(10):

HumTechRoom  TempTechRoom  TempExamRoom  HumExamRoom Machine
2018-03-04 00:45:11         82.6           NaN           NaN          NaN   22162
2018-03-04 00:45:47         80.0           NaN           NaN          NaN   22162
2018-03-04 00:45:53         78.0           NaN           NaN          NaN   22162
2018-03-04 00:46:04         75.9           NaN           NaN          NaN   22162
2018-03-04 00:46:20         73.7           NaN           NaN         51.3   22162
2018-03-04 00:46:58         71.7           NaN           NaN          NaN   22162
2018-03-04 00:47:40          NaN           NaN           NaN         53.4   22162
2018-03-04 00:47:41          NaN          14.5           NaN          NaN   22162
2018-03-04 00:47:54         74.3           NaN           NaN          NaN   22162
2018-03-04 00:47:59         76.6           NaN           NaN          NaN   22162

THis is the error message that I get:

...
line 31, in <module>
    aux = pd.concat([aux, new_col], axis=1,  sort=False)

  File ".../concat.py", line 226, in concat
    return op.get_result()

  File ".../concat.py", line 423, in get_result
    copy=self.copy)

  File ".../internals.py", line 5425, in concatenate_block_managers
    return BlockManager(blocks, axes)

  File ".../internals.py", line 3282, in __init__
    self._verify_integrity()

  File ".../internals.py", line 3493, in _verify_integrity
    construction_error(tot_items, block.shape[1:], self.axes)

  File ".../internals.py", line 4843, in construction_error
    passed, implied))

ValueError: Shape of passed values is (2, 19687), indices imply (2, 19685)

Answer 1

It seems that you are using pd.concat over the wrong axis. Remove axis=1 out of your pd.concat.. line, since axis=0 is the default as can be found in the docs

Just for your convencience. To get a cleaner dataframe, use ignore_index=True as well:

aux = pd.concat([aux, new_col], ignore_index=True,  sort=False)

Which gives a reset index back.