python - Pandas dataframe cannot convert columns datatype from object to string for further operation -


this working code, downloading excel file website. takes 40 seconds.

once run code, notice key1, key2 , key3 columns object dtypes. cleaned dataframe such key1 , key2 have alphanumeric values. still pandas keeping object dtype. need concatenate (as in ms excel) key1 , key2 create separate column called deviceid. realize cannot join 2 columns since object dtypes. how convert string can create new column?

import pandas pd import urllib.request import time  start=time.time() url="https://www.misoenergy.org/library/repository/market%20reports/20170816_da_bcsf.xls" cnstsfxls = urllib.request.urlopen(url) xlsf = pd.excelfile(cnstsfxls) dfsf = xlsf.parse("sheet1",skiprows=3) dfsf.drop(dfsf.index[len(dfsf)-1],inplace=true) dfsf.drop(dfsf[dfsf['device type'] == 'un'].index, inplace=true) dfsf.drop(dfsf[dfsf['device type'] == 'unknown'].index, inplace=true) dfsf.drop(['constraint name','contingency name', 'constraint type','flowgate name'],axis=1, inplace=true) end=time.time() print("the entire process took - ", end-start, " seconds.")

i may missing point here. if want construct column where, example, deviceid = rch417 when key1 = rch , key2 = 417, dfsf['deviceid'] = dfsf['key1'] + dfsf['key2'] work fine though both columns of type object.

try this:

# check value types dfsf.dtypes  # add desired column dfsf['deviceid'] = dfsf['key1']  + dfsf['key2']  # inspect columns of interest keep = ['key1', 'key2', 'deviceid'] df_keys = dfsf[keep] print(df_keys.dtypes)

enter image description here

print(df_keys.head())

enter image description here


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