DataFrame append generates TypeError - python-3.x

Question

I am trying to write a function to write and read transaction details to/from a .h5 file. I want to effectively use one file to store some transaction details, and when necessary, derive the details. Here's my code:
import h5py
import numpy as np
import pandas as pd
from datetime import datetime
from os import listdir
from pandas import HDFStore
def maintainLedger(mode, tick, lastBuyy = 0, lastSell = 0, quan = 0, prof = 0):
"""THIS FUNCTION WRITES AND READS TRANSACTION DETAILS.
mode = 0 - IF FILE EXITS, READ FILE
mode = 1 - IF FILE EXITS, APPEND TO FILE"""
# CHECK IF LEDGER FILE EXISTS, IF NOT CREATE A LEDGER FILE FOR THE FIRST TIME
path = r'ledger'
suff = r'h5'
flie = listdir(path)
flie = [item for item in flie if item.endswith(suff)]
if len(flie) == 0:
HDF5Data = HDFStore('ledger/ledger.h5')
# GENERATE NEW VALUES OF DATE/TIME
mi = int(datetime.now().minute)
ho = int(datetime.now().hour)
da = int(datetime.now().day)
we = int(datetime.now().isocalendar()[1])
mo = int(datetime.now().month)
ye = int(datetime.now().year)
newwData = np.array([mode, mi, ho, da, we, mo, ye, tick, lastBuyy, lastSell, quan, prof]).reshape(1, 12)
newwData = pd.DataFrame(newwData, columns = ['mode', 'mi', 'ho', 'da', 'we', 'mo', 'ye', 'tick', 'laBu', 'laSe', 'quan', 'prof'])
HDF5Data.put('data', newwData, format = 'table', data_columns = True)
HDF5Data.close()
elif len(flie) == 1:
if mode == 0:
# READ PREVIOUSLY SAVED DATA AS PANDAS DATAFRAME
readData = pd.read_hdf('ledger/ledger.h5', mode = 'r')
# DO SOMETHING...
elif mode == 1:
# GENERATE NEW VALUES OF DATE/TIME
mi = int(datetime.now().minute)
ho = int(datetime.now().hour)
da = int(datetime.now().day)
we = int(datetime.now().isocalendar()[1])
mo = int(datetime.now().month)
ye = int(datetime.now().year)
# GATHER NEW DATA INTO NUMPY ARRAY AND CONVERT TO PANDAS DATAFRAME
newwData = np.array([mode, mi, ho, da, we, mo, ye, tick, lastBuyy, lastSell, quan, prof]).reshape(1, 12)
newwData = pd.DataFrame(newwData, columns = ['mode', 'mi', 'ho', 'da', 'we', 'mo', 'ye', 'tick', 'laBu', 'laSe', 'quan', 'prof'])
# READ PREVIOUSLY SAVED DATA AS PANDAS DATAFRAME AND APPEND NEW DATA
readData = pd.read_hdf('ledger/ledger.h5', mode = 'a')
readData.append('data', newwData)
tempData = pd.read_hdf('ledger/ledger.h5', mode = 'r')
print(tempData)
else:
print('Please check input data for errors!')
if __name__ == '__main__':
maintainLedger(1, "AAPL")
When I run the code, I am getting the following error:
TypeError: cannot concatenate object of type "<class 'str'>"; only pd.Series, pd.DataFrame, and pd.Panel (deprecated) objs are valid
I have tried looking for a solution, and a quick search led me to this, which didn't solve my problem. Is there something I am doing wrong? Any advice would be appreciated.

Answer 1

import h5py
import numpy as np
import pandas as pd
from datetime import datetime
from os import listdir
from pandas import HDFStore
def maintainLedger(mode, tick = 'QUERY', lastBuyy = 0, lastSell = 0, quan = 0, prof = 0):
"""THIS FUNCTION WRITES AND READS TRANSACTION DETAILS.
mode = 0 - IF FILE EXITS, READ FILE
mode = 1 - IF FILE EXITS, APPEND TO FILE"""
# CHECK IF LEDGER FILE EXISTS, IF NOT CREATE A LEDGER FILE FOR THE FIRST TIME
path = r'ledger'
suff = r'h5'
flie = listdir(path)
flie = [item for item in flie if item.endswith(suff)]
if len(flie) == 0:
# GENERATE NEW VALUES OF DATE/TIME
mi = int(datetime.now().minute)
ho = int(datetime.now().hour)
da = int(datetime.now().day)
we = int(datetime.now().isocalendar()[1])
mo = int(datetime.now().month)
ye = int(datetime.now().year)
# GATHER NEW DATA INTO NUMPY ARRAY AND CONVERT TO PANDAS DATAFRAME
newwData = np.array([mode, mi, ho, da, we, mo, ye, tick, lastBuyy, lastSell, quan, prof]).reshape(1, 12)
newwData = pd.DataFrame(newwData, columns = ['mode', 'mi', 'ho', 'da', 'we', 'mo', 'ye', 'tick', 'laBu', 'laSe', 'quan', 'prof'])
# SAVE ALL DATA INTO .H5 FORMAT
HDF5Data = HDFStore('ledger/ledger.h5')
HDF5Data.put('data', newwData, format = 'table', data_columns = True)
HDF5Data.close()
elif len(flie) == 1:
if mode == 0:
"""THIS OPTION ENABLES CODE TO READ DATA."""
# READ PREVIOUSLY SAVED DATA AS PANDAS DATAFRAME
readData = pd.read_hdf('ledger/ledger.h5', mode = 'r')
# DO SOMETHING...
print(readData)
elif mode == 1:
"""THIS OPTION ENABLES CODE TO APPEND DATA."""
# GENERATE NEW VALUES OF DATE/TIME
mi = int(datetime.now().minute)
ho = int(datetime.now().hour)
da = int(datetime.now().day)
we = int(datetime.now().isocalendar()[1])
mo = int(datetime.now().month)
ye = int(datetime.now().year)
# GATHER NEW DATA INTO NUMPY ARRAY AND CONVERT TO PANDAS DATAFRAME
newwData = np.array([mode, mi, ho, da, we, mo, ye, tick, lastBuyy, lastSell, quan, prof]).reshape(1, 12)
newwData = pd.DataFrame(newwData, columns = ['mode', 'mi', 'ho', 'da', 'we', 'mo', 'ye', 'tick', 'laBu', 'laSe', 'quan', 'prof'])
# READ PREVIOUSLY SAVED DATA AS PANDAS DATAFRAME AND APPEND NEW DATA
readData = pd.read_hdf('ledger/ledger.h5', mode = 'r')
readData = readData.append(newwData)
# SAVE ALL DATA INTO .H5 FORMAT
HDF5Data = HDFStore('ledger/ledger.h5')
HDF5Data.put('data', readData, format = 'table', data_columns = True)
HDF5Data.close()
else:
print('Please check input data for errors!')
if __name__ == '__main__':
maintainLedger(1, 'MSFT')