Pandas | How to fill missing values in pandas dataframe

Python Pandas | df.fillna()

fillna() method of DataFrame object is used for filling missing values. refer below snippet.


  import pandas as pd
  import numpy as np
  
  #Create dataframe with numpy array
  df = pd.DataFrame(data=np.random.randint(-100,100,size=[5,5]), 
                    columns=["c1","c2","c3","c4","c5"])
  print("Original dataframe")
  print(df)
  
  # Generate NaN values
  df1 = df[df>0]
  print("Dataframe with NaN values")
  print(df1)
  
  # How to fill missing values in dataframe
  print("Dataframe with missing values replaced by 99")
  print(df1.fillna(value="99"))
  
  '''Output
  
  Original dataframe
      c1  c2  c3  c4  c5
  0 -31  -1  25 -87 -87
  1 -58  41 -56  68  59
  2 -73 -13 -23  28   2
  3 -71  74  15 -43 -32
  4  22 -30 -69  50  63
  Dataframe with NaN values
        c1    c2    c3    c4    c5
  0   NaN   NaN  25.0   NaN   NaN
  1   NaN  41.0   NaN  68.0  59.0
  2   NaN   NaN   NaN  28.0   2.0
  3   NaN  74.0  15.0   NaN   NaN
  4  22.0   NaN   NaN  50.0  63.0
  Dataframe with missing values replaced by 99
      c1  c2  c3  c4  c5
  0  99  99  25  99  99
  1  99  41  99  68  59
  2  99  99  99  28   2
  3  99  74  15  99  99
  4  22  99  99  50  63
  
  '''