Formas de aplicar LEFT, RIGHT, MID en Pandas

Muchas veces necesitamos extraer caracteres específicos presentes dentro de una string en el marco de datos de Pandas. Para resolver este problema, tenemos el concepto de Izquierda, Derecha y Medio en pandas.

Ejemplo 1: extraer caracteres de la izquierda

# importing pandas library
import pandas as pd
  
# creating and initializing a list 
Cars = ['1000-BMW','2000-Audi','3000-Volkswagen',
        '4000-Datsun','5000-Toyota','6000-Maruti Suzuki']
  
# creating a pandas dataframe
df = pd.DataFrame(Cars, columns= ['Model_name'])
  
# Extracting characters from right side
# using slicing and storing result in 
# 'Left'
Left = df['Model_name'].str[:4]
  
print(Left)

Producción :

0    1000
1    2000
2    3000
3    4000
4    5000
5    6000
Name: Model_name, dtype: object

Ejemplo 2: extraer caracteres de la derecha

# importing pandas library
import pandas as pd
  
# creating and initializing a list 
Cars = ['ID-11111-BMW','ID-22222-Volkswagen',
        'ID-33333-Toyota','ID-44444-Hyundai ',
        'ID-55555-Datsun','ID-66666-Mercedes']
  
# creating a pandas dataframe
df = pd.DataFrame(Cars, columns= ['Model_name'])
  
# Extracting characters from left side using
# slicing and storing result in 'Right'
Right = df['Model_name'].str[4:8]
  
print (Right)

Producción :

0    11111
1    22222
2    33333
3    44444
4    55555
5    66666
Name: Model_name, dtype: object

Ejemplo 3: extraer caracteres del medio

# importing pandas library
import pandas as pd
  
# creating and initializing a list 
Cars = ['ID-11111-BMW','ID-22222-Volkswagen',
        'ID-33333-Toyota','ID-44444-Hyundai ',
        'ID-55555-Datsun','ID-66666-Mercedes']
  
# creating a pandas dataframe
df = pd.DataFrame(Cars, columns= ['Model_name'])
  
# Extracting characters from Middle using 
# slicing and storing result in 'Mid'
Mid = df['Model_name'].str[4:8]
  
print (Mid)

Producción :

0    1111
1    2222
2    3333
3    4444
4    5555
5    6666
Name: Model_name, dtype: object

Ejemplo 4: Antes de un símbolo usando la función str.split()

# importing pandas library
import pandas as pd
  
# creating and initializing a list 
Cars = ['1000-BMW','2000-Audi',
        '3000-Volkswagen','4000-Datsun',
        '5000-Toyota','6000-Maruti Suzuki']
  
# creating a pandas dataframe
df = pd.DataFrame(Cars, columns= ['Model_name'])
  
# Extracting characters before symbol "-"
# using srt.strip() and str[0]
# and storing result to 'Before_symbol'
Before_symbol = df['Model_name'].str.split('-').str[0]
  
print (Before_symbol)

Producción :

0    1000
1    2000
2    3000
3    4000
4    5000
5    6000
Name: Model_name, dtype: object

Ejemplo 5:   Entre símbolos idénticos usando la función str.split()

# importing pandas library
import pandas as pd
  
# creating and initializing a list 
Cars = ['M3-1906-BMW','M5-2096-Audi',
        'M11-3096-Volkswagen','M9-4096-Datsun',
        'M8-5096-Toyota','M23-6096-Maruti Suzuki']
  
# creating a pandas dataframe
df = pd.DataFrame(Cars, columns= ['Model_name'])
  
# Extracting characters between symbol "-"
# using srt.strip() and str[1]
# and storing result to 'Before_symbol'
BetweenTwoSymbols = df['Model_name'].str.split('-').str[1]
  
print (BetweenTwoSymbols)

Producción :

0    1906
1    2096
2    3096
3    4096
4    5096
5    6096
Name: Model_name, dtype: object