PYTHON

filter rows pandas

newdf = df[(df.origin == "JFK") & (df.carrier == "B6")]

filter rows dataframe pandas

# filter Rows Based on condition
df[df["Courses"] == 'Spark'] 
df.loc[df['Courses'] == value]
df.query("Courses == 'Spark'")
df.loc[df['Courses'] != 'Spark']
df.loc[df['Courses'].isin(values)]
df.loc[~df['Courses'].isin(values)]

# filter Multiple Conditions using Multiple Columns
df.loc[(df['Discount'] >= 1000) & (df['Discount'] <= 2000)]
df.loc[(df['Discount'] >= 1200) & (df['Fee'] >= 23000 )]

# Using lambda function
df.apply(lambda row: row[df['Courses'].isin(['Spark','PySpark'])])

# filter columns that have no None & nana values
df.dropna()

# Other examples
df[df['Courses'].str.contains("Spark")]
df[df['Courses'].str.lower().str.contains("spark")]
df[df['Courses'].str.startswith("P")]