DataFrame.head() to get five rows of data from the DataFrame

Returns the first n rows of the DataFrame.
n : int, defalut is 5, number of rows to return.

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

Output ( by default we get 5 rows )

   NAME  ID  MATH  ENGLISH
0  Ravi   1    80       80
1  Raju   2    40       70
2  Alex   3    70       40
3   Ron   4    70       50
4  King   5    70       60

Let us change the last line only by asking 2 records

print(df.head(2))

Output

   NAME  ID  MATH  ENGLISH
0  Ravi   1    80       80
1  Raju   2    40       70

Create DataFrame from Excel file by using read_excel() and displaying first n records.

import pandas as pd 
df = pd.read_excel('D:\student.xlsx',index_col='id')
print(df.head(3))

Reading from csv file to create DataFrame and displaying first n records.

import pandas as pd 
df= pd.read_csv('D:\\my_data\\student.csv') # DataFrame from csv file data
print(df.head(2))# first 2 rows

By using Reading from csv file to create DataFrame you can get a tuple showing rows and columns.

import pandas as pd 
df = pd.read_excel('D:\student.xlsx',index_col='id')
print(df.shape)

Output

(35, 4)

You can check the code and output at Exercise 1

str.contains.sum()

Using head() output as string

Using to_string() we can convert the object to string and then add.
We used str() to convert tuple element as integer to string before adding.

str1="Rows:" + str(df.shape[0])+ ",Columns:"+str(df.shape[1])
str1=str1+ "\n"+df.head(2).to_string()

Pandas tail() read_csv() read_excel() to_excel()

Numpy arrays Python & MySQL Python- Tutorials

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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