Pandas DataFrame iloc

df2 = df.iloc[:0] # create dataframe of same structure or columns

import pandas as pd 
my_dict={'NAME':['Ravi','Raju','Alex','Ron','King','Jack'],
         'ID':[1,2,3,4,5,6],'MATH':[30,40,50,60,70,80],
         'ENGLISH':[20,30,40,50,60,70]}
df = pd.DataFrame(data=my_dict)

print(df.iloc[0]) # First rows 

NAME       Ravi
ID            1
MATH         30
ENGLISH      20
Name: 0, dtype: object

Second row

print(df.iloc[1])

NAME       Raju
ID            2
MATH         40
ENGLISH      30
Name: 1, dtype: object

Value at position

print(df.iloc[1,2]) # 40 

print(df.iloc[:2])

   NAME  ID  MATH  ENGLISH
0  Ravi   1    30       20
1  Raju   2    40       30

print(df.iloc[::]) # all rows all columns
print(df.iloc[:,:]) # all rows all columns 
print(df.iloc[:,2]) # all rows class column 

print(df.iloc[[0]]) 

   NAME  ID  MATH  ENGLISH
0  Ravi   1    30       20

Last record

print(df.iloc[-1])

NAME       Jack
ID            6
MATH         80
ENGLISH      70
Name: 5, dtype: object

print(df.iloc[-1,2]) # 80

Range of rows

print(df.iloc[2:5]) # range of records 

   NAME  ID  MATH  ENGLISH
2  Alex   3    50       40
3   Ron   4    60       50
4  King   5    70       60

First and Last record

print(df.iloc[[0,-1]]) # first and last records

   NAME  ID  MATH  ENGLISH
0  Ravi   1    30       20
5  Jack   6    80       70

Alternate rows of the DataFrame

print(df.iloc[::2]) alternate rows
print(df.iloc[::3]) # All third rows starting from first

iloc with Callable function

print(df.iloc[lambda x: x.index % 2 == 0]) # All even rows based on Index value
print(df.iloc[lambda x: [4,6,12],:]) # records based on index value
print(df.iloc[lambda x: list(x.id % 2 == 0)]) # All even rows based on a column value
print(df.iloc[lambda x: list(x.mark>90),:]) # records based condition

Using boolean array

print(df.iloc[:,[True,False,True,False,True]]) # show all rows with matching columns 

df2=df.iloc[0:3] # New DataFrame with 3 rows 
print(df2.iloc[[True,False,True]]) # Matching rows based on Index value

Summary of using iloc

print(df.iloc[::]) # all rows 
print(df.iloc[0]) # first record
print(df.iloc[1]) # second record
print(df.iloc[1,3]) # second record 3rd element ( 85 ) 
print(df.iloc[:,1]) # All rows name column

print(df.iloc[-1]) # show last record
print(df.iloc[[-1]]) # show last record in full 

print(df.iloc[:2]) # first two records
print(df.iloc[:-2]) # All records except last two 
print(df.iloc[-2]) # 2nd from last record 
print(df.iloc[-2:]) # Last two records   
print(df.iloc[2:5]) # range of records, 3rd to 5th
print(df.iloc[[0,-1]]) # first and last row 

print(df.iloc[::2]) # alternate rows from DataFrame
print(df.iloc[::3]) # All third rows starting from first 

Records with matching conditions

print(df[df['MATH']>=50])

   NAME  ID  MATH  ENGLISH
2  Alex   3    50       40
3   Ron   4    60       50
4  King   5    70       60
5  Jack   6    80       70

Update record based on iloc

df.iloc[33, df.columns.get_loc('mark')] = 100

df.iloc[:, df.columns.get_loc('mark')] = 100

df.iloc[df['mark']>=90, df.columns.get_loc('mark')] = 100

df.iloc[df['name']=='Kenn Rein',df.columns.get_loc('name')]='abcd'

Updating using for loop

for i in df.index:
    df.iloc[i,3]=51 # update the 4th column with 51

Subhendu Mohapatra

Author & Instructor at plus2net

I write and maintain practical tutorials on Python, PHP, SQL, JavaScript, HTML, jQuery, and web development at plus2net. The tutorials focus on clear explanations, working examples, and code that readers can test and adapt while learning.

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