For a dataframe df, one can use any of the following:
1)len(df.index)
2)df.shape[0]
3)df[df.columns[0]].count() (slowest, but avoids counting NaN values in the first column)
df = pd.DataFrame({"Letters": ["a", "b", "c"], "Numbers": [1, 2, 3]})
index = df.index
number_of_rows = len(index)
>>> df.count(axis='columns')
0 3
1 2
2 3
3 3
4 3
dtype: int64
count_row = df.shape[0] # Gives number of rows
count_col = df.shape[1] # Gives number of columns
len(df)
#print
print('row = ' + str(len(df)))
len(df)