Important Query for Pandas Dataframe

dataframe_func_query.txt

# search with and/or condition
  df4 = df3.query('(From=="AHH" & To=="BBH") | (From=="BBH" & To=="AHH")')
                                    OR
  data.loc[(data["Gender"]=="Female") & (data["Education"]=="Not Graduate") & (data["Loan_Status"]=="Y"), ["Gender","Education","Loan_Status"]]

# Rows to columns
  df = df.stack().reset_index().rename(columns={'level_0':'From','level_1':'To', 0:'Hours'})

# Join two df like sql join
  df1 = df1.merge(record_df, on='location_code', how='outer', suffixes=('_x', '_y'))

# concate multiple df's
  master_df = pd.concat([master_df, df], ignore_index=True
  
# applymap function
df.applymap(lambda x:x*2)

# add new column in df
df.assign(Score3 = [56,86,77,45,73,62,74,89,71])

# df date string to pandas date object
  df['date'] = pd.to_datetime(df['date'])
                   OR
  df = pd.read_csv('file.csv', parse_dates=['Date'])