Pandas | How to drop rows with missing values in dataframe

Python Pandas dropna

dropna() method of DataFrame object is used for dropping rows having 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(-10,100,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 drop rows having  missing values
  print("Dataframe with dropped rows having NaN values")
  print(df1.dropna())
  
  '''Output    
  Original dataframe
      c1  c2  c3  c4  c5
  0  52  14   0  39  22
  1  88  58  66  51  36
  2  93  28  87   1  32
  3  66  19  61  70  43
  4  98  58  64 -10  32
  Dataframe with NaN values
      c1  c2    c3    c4  c5
  0  52  14   NaN  39.0  22
  1  88  58  66.0  51.0  36
  2  93  28  87.0   1.0  32
  3  66  19  61.0  70.0  43
  4  98  58  64.0   NaN  32
  Dataframe with dropped rows having NaN values
      c1  c2    c3    c4  c5
  1  88  58  66.0  51.0  36
  2  93  28  87.0   1.0  32
  3  66  19  61.0  70.0  43    
  '''