Pandas cookbook

Read the excel file 

>>> df = pd.read_excel('/home/ambiorixg12/Downloads/500.xlsx')

Save values as list

lst= df.values.tolist()

Count values  from the list 

 len(lst)

500

Print first and last entry

>> print(lst[0],'\n',lst[-1])

['Gaston', 'Willie', 6009.0, nan, 'Howells Ferry', 'Rd', nan, nan, 'Mobile', 'AL', 36618, '(251) 304-1631', 'Male'] 

 ['Paulo', 'Frank', 1801.0, nan, 'Ridgecrest', 'St', nan, nan, 'Valdosta', 'GA', 31601, '(229) 671-9476', 'Male']

Get columns name

headers = df.columns.tolist()

Data type

print(df.dtypes)

-----

Create a dict with the first value and include the column names

God version

 df = pd.read_excel('/home/ambiorixg12/Downloads/500.xlsx')

 c={df.columns.tolist()[a]:df.values.tolist()[0][a] for a in range(len(df.values.tolist()[0])) }

get the first value of are data set

>>> v=[a for a in  df.values.tolist()[0]]  

>>> 

>>> 

>>> 

>>>  ge colum names

>>> h=[a for a in  df.columns.tolist()]

>>>  create are dict

>>> new={h[v.index(a)]:a for a in v}

>>> print(new)

{'Last Name': 'Gaston', 'First Name': 'Willie', 'House Number': 6009.0, 'Pre-directional': nan, 'Street': 'Howells Ferry', 'Street Suffix': 'Rd', 'City': 'Mobile', 'State': 'AL', 'Zip Code': 36618, 'Phone Number': '(251) 304-1631', 'Gender': 'Male'}

>>> 

Or simplify version

>>> new={h[v.index(a)]:a for a in [a for a in  df.values.tolist()[0]]}

---getting header

>>> c={df.columns.tolist()[a] for a in range(len(df.values.tolist()[0])) }

>>> c

{'First Name', 'Gender', 'Pre-directional', 'State', 'House Number', 'Post-directional', 'Last Name', 'Phone Number', 'Street', 'Zip Code', 'City', 'Apartment Number', 'Street Suffix'}

>>> 

info=requests.get('https://ipinfo.io/json').json() 

>>> df = pd.DataFrame.from_dict(info, orient='index', columns=['value'])