What is the most efficient way to loop through dataframes with pandas?

In Python, you have three options to loop through DataFrames with Pandas.

By index (simplest):

>>> for index in df.index:
...     print ("df[" + str(index) + "]['B']=" + str(df['B'][index]))

With iterrows (most used):

>>> for index, row in df.iterrows():
...     print ("df[" + str(index) + "]['B']=" + str(row['B']))

With itertuples (fastest):

>>> for row in df.itertuples():
...     print ("df[" + str(row.Index) + "]['B']=" + str(row.B))

Three options display something like:

df[0]['B']=125
df[1]['B']=415
df[2]['B']=23
df[3]['B']=456
df[4]['B']=189
df[5]['B']=456
df[6]['B']=12

In Python, you have three options to loop through dataframes with Pandas.

By index (simplest):

>>> for index in df.index:
...     print ("df[" + str(index) + "]['B']=" + str(df['B'][index]))

With iterrows (most used):

>>> for index, row in df.iterrows():
...     print ("df[" + str(index) + "]['B']=" + str(row['B']))

With itertuples (fastest):

>>> for row in df.itertuples():
...     print ("df[" + str(row.Index) + "]['B']=" + str(row.B))

Three options display something like:

df[0]['B']=125
df[1]['B']=415
df[2]['B']=23
df[3]['B']=456
df[4]['B']=189
df[5]['B']=456
df[6]['B']=12

In Python, you have three options to loop through dataframes with Pandas.

By index (simplest):

>>> for index in df.index:
...     print ("df[" + str(index) + "]['B']=" + str(df['B'][index]))

With iterrows (most used):

>>> for index, row in df.iterrows():
...     print ("df[" + str(index) + "]['B']=" + str(row['B']))

With itertuples (fastest):

>>> for row in df.itertuples():
...     print ("df[" + str(row.Index) + "]['B']=" + str(row.B))

Three options display something like:

df[0]['B']=125
df[1]['B']=415
df[2]['B']=23
df[3]['B']=456
df[4]['B']=189
df[5]['B']=456
df[6]['B']=12