Create pandas DataFrame and add columns and rows to it

import pandas as pd
  
#first method - create empty dataframe
df = pd.DataFrame()

# append columns and rows to this dataframe
df['username'] = ['john', 'neil', 'curtis']
df['status'] = ['active', 'disabled', 'active']
print(df)

#----------------------------------------------------------------------------------#

#second method - create dataframe with columns
df = pd.DataFrame(columns = ['username', 'status'])

# append rows to the abo
df = df.append({'username' : 'john', 'status' : 'active'}, ignore_index = True)
df = df.append({'username' : 'neil', 'status' : 'disabled'}, ignore_index = True)
df = df.append({'username' : 'curtis', 'status' : 'active'}, ignore_index = True)
print(df)

#----------------------------------------------------------------------------------#

#make data frame with rows having - NaN values at index - a, b and c
df = pd.DataFrame(columns = ['username', 'status'], index = ['a', 'b', 'c'])
print(df)
#  +---+----------+--------+
#  |   | username | status |
#  +---+----------+--------+
#  | a |      NaN |    NaN |
#  | b |      NaN |    NaN |
#  | c |      NaN |    NaN |
#  +---+----------+--------+

# add rows at already created indexes
df.loc['a'] = ['john', 'active']
df.loc['b'] = ['neil', 'disabled']
df.loc['c'] = ['curtis', 'active']
print(df)