1. Python
  2. Create a List of Strings in a Pandas DataFrame | Set 2

Create a List of Strings in a Pandas DataFrame | Set 2

Note. To link to the CSV file used in the code, click here .

Solution # 1: To access the data of each row of DataFrame.iloc Pandas data, we can use the DataFrame attribute .iloc and then add the data of each row to the end of the list.

# import pandas as pd

import pandas as pd

 
# Create data frame

df = pd.DataFrame ({ `Date` : [ `10/2 / 2011` , `11/2 / 2011` , ` 12/2 / 2011` , `13/2 / 11` ],

`Event` : [ `Music` , ` Poetry` , `Theater` , ` Comedy` ],

`Cost` : [ 10000 , 5000 , 15000 , 2000 ]})

 
# Raspe chat dataframe

print (df)

Output:

We will now use the DataFrame.iloc attribute to access the values ​​of each row in the data frame, and then DataFrame.iloc a list from it.

# Create empty list

Row_list = []

  
# Iterate over each line

for i in range ((df.shape [ 0 ])):

  

# Using iloc to access values ​​

# current line denoted by & quot; i & quot;

Row_list.append ( list (df.iloc [i,:]))

 
# Print list

print (Row_list)

Output:

As we can see in the output, we have successfully extracted each row of the given dataframe into a list. Like any other Python list, we can perform any operation on the list of the retrieved list.

# Find the length again
# list created

print ( len (Row_list))

  
# Print first 3 items

print (Row_list [: 3 ])

Output:

Solution # 2. To access your data every DataFrame.iat row of Pandas data, we can use the DataFrame.iat attribute and then add each row`s data to the end of the list.

# import pandas as pd

import pandas as pd

 
# Create data frame

df = pd.DataFrame ({ ` Date` : [ `10/2 / 2011` , `11/2 / 2011` , ` 12/2 / 2011` , `13/2 / 11` ],

  `Event` : [ ` Music` , ` Poetry` , `Theater` , `Comedy` ],

`Cost` : [ 10000 , 5000 , 15000 , 2000 ]})

 
# Create empty list

Row_list = []

  
# Iterate over each line

for i in range ((df.shape [ 0 ])):

# Create a list to store data

Current line no.

  cur_row = []

 

# iterate over all columns

for j in range (df.shape [ 1 ]):

 

# add each data

# column to list

cur_row.append (df.iat [i, j])

  

  # add current line to list

Row_list.append (cur_row)

 
# Print list

print (Row_list)

Output:

# Find the length again
# list created

print ( len (Row_list))

 
# Print first 3 items

print (Row_list [: 3 ])

Output: