pandas python how to count the number of records or rows in a dataframe

Question

Obviously new to Pandas  How can i simply count the number of records in a dataframe   I would have thought some thing as simple as this would do it and i can t seem to even find the answer in searches   probably because it is too simple   cnt   df count print cnt   the above code actually just prints the whole df

User · Accepted Answer

Regards to your question    counting one Field   I decided to make it a question  but I hope it helps     Say I have the following DataFrame  import numpy as np import pandas as pd  df   pd DataFrame np random normal 0  1   5  2    columns   A    B      You could count a single column by  df A count    or df  A   count     both evaluate to 5   The cool thing  or one of many w r t  pandas  is that if you have NA values  count takes that into consideration   So if I did  df  A   1  2    np NAN df count     The result would be   A    3  B    5

User · Answer

Simply  row num    df shape 0      gives number of rows  here s the example   import pandas as pd import numpy as np  In  322   df   pd DataFrame np random randn 5 2   columns   col 1    col 2     In  323   df Out 323          col 1     col 2 0 -0 894268  1 309041 1 -0 120667 -0 241292 2  0 076168 -1 071099 3  1 387217  0 622877 4 -0 488452  0 317882  In  324   df shape Out 324    5  2   In  325   df shape 0       Gives no  of rows records Out 325   5  In  326   df shape 1       Gives no  of columns Out 326   2

User · Answer

To get the number of rows in a dataframe use   df shape 0     and df shape 1  to get the number of columns    As an alternative you can use   len df    or  len df index     and len df columns  for the columns   shape is more versatile and more convenient than len    especially for interactive work  just needs to be added at the end   but len is a bit faster  see also this answer    To avoid  count   because it returns the number of non-NA null observations over requested axis  len df index  is faster   import pandas as pd import numpy as np  df   pd DataFrame np arange 24  reshape 8  3  columns   A    B    C    df  A   5  np nan df   Out        A   B   C   0   0   1   2   1   3   4   5   2   6   7   8   3   9  10  11   4  12  13  14   5 NaN  16  17   6  18  19  20   7  21  22  23   timeit df shape 0    100000 loops  best of 3  4 22   s per loop   timeit len df    100000 loops  best of 3  2 26   s per loop   timeit len df index    1000000 loops  best of 3  1 46   s per loop   df   len    is just a call to len df index   import inspect  print inspect getsource pd DataFrame   len       Out        def   len   self                Returns length of info axis  but here we use the index               return len self index    Why you should not use count    df count     Out    A    7   B    8   C    8

User · Answer

The Nan example above misses one piece  which makes it less generic  To do this more  generically  use df  column name   value counts   This will give you the counts of each value in that column   d   A   A   A   B   C   C                        -1     for simplicity  df pd DataFrame d  df columns   col1   df  col1   value counts          5 A     3 C     2 -1    1 B     1 dtype  int64    len df  give you 12  so we know the rest must be Nan s of some form  while also having a peek into other invalid entries  especially when you might want to ignore them like -1  0       also

User · Answer

Simple method to get the records count  df count   0

[count] pandas python how to count the number of records or rows in a dataframe

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