Pandas get the most frequent values of a column

Question

i have this dataframe   0 name data 1 alex asd 2 helen sdd 3 alex dss 4 helen sdsd 5 john sdadd   so i am trying to get the most frequent value or values in this case its values  so what i do is   dataframe  name   value counts   idxmax     but it returns only the value  Alex even if it Helen appears two times as well

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to get top 5   dataframe  name   value counts   0 5

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Here s one way   df  name   value counts   df  name   value counts      df  name   value counts   max      which prints   helen    2 alex     2 Name  name  dtype  int64

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To get the n most frequent values  just subset  value counts   and grab the index     get top 10 most frequent names n   10 dataframe  name   value counts    n  index tolist

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You can use this to get a perfect count  it calculates the mode a particular column  df  name   value counts

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To get the top five most common names   dataframe  name   value counts   head

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n is used to get the number of top frequent used items n   2  a dataframe  name   value counts    n  index tolist    dataframe  quot name quot   value counts   a

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df  name   value counts    5  sort values ascending False    The value counts will return a count object of pandas core series Series and sort values ascending False  will get you the highest values first

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You could use  apply and pd value counts to get a count the occurrence of all the names in the name column   dataframe  name   apply pd value counts

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By using mode   df name mode   Out 712    0     alex 1    helen dtype  object

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Use  df  name   mode    or df  name   value counts   idxmax

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Not Obvious  But Fast    f  u   pd factorize df name values  counts   np bincount f  u counts    counts max     array   alex    helen    dtype object

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my best solution to get the first is   df  my column   value counts   sort values ascending False  argmax

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Simply use this       dataframe  name   value counts   nlargest n    The functions for frequencies largest and smallest are    nlargest   for mostfrequent  n  values nsmallest   for least frequent  n  values

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You could try argmax like this     dataframe  name   value counts   argmax   Out 13    alex       The value counts will return a count object of pandas core series Series and argmax could be used to achieve the key of max values

[python] Pandas get the most frequent values of a column

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