damn_it.py

from pandas import DataFrame, Series

a = [1, 2, 3, 4]
b = a.append(5)

print(a)
# [1, 2, 3, 4, 5]
print(b)
# None

# This makes sense as append modifies the original list but does NOT create a new list, so b is set to None. Pandas however..is the opposite

data = [['Roger Federer', 20], ['Rafael Nadal', 16]]
column_titles = ['Tennis Player', 'Number of Grand Slams']
data_frame = DataFrame(data=data, columns=column_titles)

print(data_frame)
'''
   Tennis Player Number of Grand Slams
0  Roger Federer                    20
1   Rafael Nadal                    16
'''

# So far so good

new_row = Series(['Novak Djokovic', 12], index=column_titles)

data_frame.append(new_row, ignore_index=True)
print(data_frame)
'''
   Tennis Player Number of Grand Slams
0  Roger Federer                    20
1   Rafael Nadal                    16
'''

# WAIT WHAT THE HELL IS THIS? Turns out, append returns a new data frame that you have to reassign
data_frame = data_frame.append(new_row, ignore_index=True)
print(data_frame)
'''
    Tennis Player  Number of Grand Slams
0   Roger Federer                     20
1    Rafael Nadal                     16
2  Novak Djokovic                     12
'''

# It works but god damn it, why does pandas go against the "edit object in place" paradigm that every other programming language uses