Compare two columns using pandas

Question

Using this as a starting point   a      10    1 2    4 2      15    70    0 03      8    5    0    df   pd DataFrame a  columns   one    two    three     Out 8      one  two three 0   10  1 2   4 2 1   15  70   0 03 2    8   5     0   I want to use something like an if statement within pandas    if df  one    gt   df  two   and df  one    lt   df  three        df  que     df  one     Basically  check each row via the if statement  create new column    The docs say to use  all but there is no example

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Use np select if you have multiple conditions to be checked from the dataframe and output a specific choice in a different column  conditions   condition1   condition2   choices   choice1   chocie2    df  new column   np select  condtion choice default     Note  No of conditions and no of choices should match  repeat text in choice if for two different conditions you have same choices

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One way is to use a Boolean series to index the column df  one    This gives you a new column where the True entries have the same value as the same row as df  one   and the False values are NaN   The Boolean series is just given by your if statement  although it is necessary to use  amp  instead of and     gt  gt  gt  df  que     df  one    df  one    gt   df  two     amp   df  one    lt   df  three      gt  gt  gt  df     one two three   que 0   10  1 2 4 2      10 1   15  70  0 03    NaN 2   8   5   0       NaN   If you want the NaN values to be replaced by other values  you can use the fillna method on the new column que  I ve used 0 instead of the empty string here    gt  gt  gt  df  que     df  que   fillna 0   gt  gt  gt  df     one two three   que 0   10  1 2   4 2    10 1   15   70  0 03     0 2    8    5     0     0

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I think the closest to the OP s intuition is an inline if statement   df  que      df  one   if   df  one    gt   df  two    and  df  one    lt   df  three

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You could use apply   and do something like this df  que     df apply lambda x   x  one   if x  one    gt   x  two   and x  one    lt   x  three   else  quot  quot   axis 1   or if you prefer not to use a lambda def que x       if x  one    gt   x  two   and x  one    lt   x  three            return x  one       return    df  que     df apply que  axis 1

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You could use np where  If cond is a boolean array  and A and B are arrays  then  C   np where cond  A  B    defines C to be equal to A where cond is True  and B where cond is False   import numpy as np import pandas as pd  a      10    1 2    4 2      15    70    0 03      8    5    0    df   pd DataFrame a  columns   one    two    three     df  que     np where  df  one    gt   df  two     amp   df  one    lt   df  three                           df  one    np nan    yields    one  two three  que 0  10  1 2   4 2   10 1  15   70  0 03  NaN 2   8    5     0  NaN     If you have more than one condition  then you could use np select instead  For example  if you wish df  que   to equal df  two   when df  one    lt  df  two    then  conditions          df  one    gt   df  two     amp   df  one    lt   df  three          df  one    lt  df  two     choices    df  one    df  two     df  que     np select conditions  choices  default np nan    yields    one  two three  que 0  10  1 2   4 2   10 1  15   70  0 03   70 2   8    5     0  NaN   If we can assume that df  one    gt   df  two   when df  one    lt  df  two   is False  then the conditions and choices could be simplified to  conditions         df  one    lt  df  two        df  one    lt   df  three     choices    df  two    df  one       The assumption may not be true if df  one   or df  two   contain NaNs      Note that   a      10    1 2    4 2      15    70    0 03      8    5    0    df   pd DataFrame a  columns   one    two    three      defines a DataFrame with string values  Since they look numeric  you might be better off converting those strings to floats   df2   df astype float    This changes the results  however  since strings compare character-by-character  while floats are compared numerically   In  61    10   lt    4 2  Out 61   True  In  62   10  lt   4 2 Out 62   False

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You can use  equals for columns or entire dataframes   df  col1   equals df  col2      If they re equal  that statement will return True  else False

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Wrap each individual condition in parentheses  and then use the  amp  operator to combine the conditions   df loc  df  one    gt   df  two     amp   df  one    lt   df  three      que     df  one     You can fill the non-matching rows by just using    the  not  operator  to invert the match   df loc     df  one    gt   df  two     amp   df  one    lt   df  three       que          You need to use  amp  and   rather than and and not because the  amp  and   operators work element-by-element   The final result   df Out 8      one  two three que 0  10  1 2   4 2  10 1  15   70  0 03     2   8    5     0

User · Answer

Use lambda expression  df df apply lambda x  x  col1      x  col2    axis   1

[python] Compare two columns using pandas

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