Pandas | How to use df.apply() in pandas dataframe

Python Pandas df.apply()

apply() method of DataFrame object apply a function along an axis of the DataFrame. refer below snippet for the same.


  import pandas as pd
  import numpy as np
  
  
  #Create dataframe with numpy array
  df = pd.DataFrame(np.random.randint(10,100,size=[5,5]), 
                    columns=["c1","c2","c3","c4","c5"])
  print("Original dataframe")
  print(df)
  
  
  #How to use df.apply() in pandas
  # In the below code function np.sqrt would be applied to dataframe
  print("applying numpy function as paramter in df.apply")
  df1 = df.apply(np.sqrt)
  print(df1)
  
  
  
  #Using lambda function in df.apply(), for squaring the values in dataframe
  print("applying lambda function as paramter in df.apply")
  my_func = lambda x:x*x
  df2 = df.apply(my_func)
  print(df2)
  
  
  
  
  
  '''Output
  
  Original dataframe
      c1  c2  c3  c4  c5
  0  30  39  62  42  14
  1  42  11  87  18  61
  2  81  43  16  77  72
  3  57  47  94  31  80
  4  58  92  96  31  19
  applying numpy function as paramter in df.apply
            c1        c2        c3        c4        c5
  0  5.477226  6.244998  7.874008  6.480741  3.741657
  1  6.480741  3.316625  9.327379  4.242641  7.810250
  2  9.000000  6.557439  4.000000  8.774964  8.485281
  3  7.549834  6.855655  9.695360  5.567764  8.944272
  4  7.615773  9.591663  9.797959  5.567764  4.358899
  applying lambda function as paramter in df.apply
        c1    c2    c3    c4    c5
  0   900  1521  3844  1764   196
  1  1764   121  7569   324  3721
  2  6561  1849   256  5929  5184
  3  3249  2209  8836   961  6400
  4  3364  8464  9216   961   361
  '''