Csv file for python practice download

Python CSV File Reading and Writing - Exercises, Practice, Solution

Last update on August 19 2022 21:51:51 [UTC/GMT +8 hours]

Python CSV File Reading and Writing [11 exercises with solution]

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1. Write a Python program to read each row from a given csv file and print a list of strings. Go to the editor
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2. Write a Python program to read a given CSV file having tab delimiter. Go to the editor
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3. Write a Python program to read a given CSV file as a list.
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4. Write a Python program to read a given CSV file as a dictionary. Go to the editor
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5. Write a Python program to read a given CSV files with initial spaces after a delimiter and remove those initial spaces. Go to the editor
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6. Write a Python program that reads a CSV file and remove initial spaces, quotes around each entry and the delimiter. Go to the editor
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7. Write a Python program to read specific columns of a given CSV file and print the content of the columns. Go to the editor
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8. Write a Python program that reads each row of a given csv file and skip the header of the file. Also print the number of rows and the field names. Go to the editor
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9. Write a Python program to create an object for writing and iterate over the rows to print the values. Go to the editor
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10. Write a Python program to write a Python list of lists to a csv file. After writing the CSV file read the CSV file and display the content. Go to the editor
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11. Write a Python program to write a Python dictionary to a csv file. After writing the CSV file read the CSV file and display the content. Go to the editor
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Python Code Editor:

More to Come !

Do not submit any solution of the above exercises at here, if you want to contribute go to the appropriate exercise page.

Test your Python skills with w3resource's quiz

Python: Tips of the Day

Given each iterable to construct a tuple by adding an index:

>>> a = ['Hello', 'world', '!']
>>> list[enumerate[a]]
[[0, 'Hello'], [1, 'world'], [2, '!']]

Pandas sample student DataFrame

Pandas

To create your sample DataFrame, download the excel file or csv file and then use read_excel[] or read_csv[] to create DataFrame. OR copy the code below to create the same sample DataFrame.
From Excel or CSV file to DataFrame code is available below.
Download sample [ Excel file ] student.xlsx csv file: student.csv

import pandas as pd
dt={'id': {0: 1,1: 2,2: 3,3: 4,4: 5,5: 6,6: 7,7: 8,8: 9,9: 10,10: 11,11: 12,
  12: 13,13: 14,14: 15,15: 16,16: 17,17: 18,18: 19,19: 20,20: 21,21: 22,
  22: 23,23: 24,24: 25,25: 26,26: 27,27: 28,28: 29,29: 30,30: 31,31: 32,32: 33,
  33: 34,34: 35},
 'name': {0: 'John Deo',1: 'Max Ruin',2: 'Arnold',3: 'Krish Star',4: 'John Mike',
  5: 'Alex John',6: 'My John Rob',7: 'Asruid',8: 'Tes Qry',9: 'Big John',
  10: 'Ronald',11: 'Recky',12: 'Kty',13: 'Bigy',14: 'Tade Row',15: 'Gimmy',
  16: 'Tumyu',17: 'Honny',18: 'Tinny',19: 'Jackly',20: 'Babby John',21: 'Reggid',
  22: 'Herod',23: 'Tiddy Now',24: 'Giff Tow',25: 'Crelea',26: 'Big Nose',
  27: 'Rojj Base',28: 'Tess Played',29: 'Reppy Red',30: 'Marry Toeey',
  31: 'Binn Rott',32: 'Kenn Rein',33: 'Gain Toe',34: 'Rows Noump'},
  'class': {0: 'Four', 1: 'Three',2: 'Three',3: 'Four',4: 'Four', 5: 'Four',
  6: 'Five',7: 'Five',8: 'Six',9: 'Four',10: 'Six',11: 'Six',12: 'Seven',
  13: 'Seven',14: 'Four',15: 'Four',16: 'Six',17: 'Five',18: 'Nine',19: 'Nine',
  20: 'Four',21: 'Seven',22: 'Eight',23: 'Seven',24: 'Seven',25: 'Seven',
  26: 'Three',27: 'Seven',28: 'Seven',29: 'Six',30: 'Four',31: 'Seven',32: 'Six',
  33: 'Seven',34: 'Six'},'mark': {0: 75,1: 85,2: 55,3: 60,4: 60,5: 55,6: 78,
  7: 85,8: 78,9: 55,10: 89,11: 94,12: 88,13: 88,14: 88,15: 88,16: 54,17: 75,
  18: 18,19: 65,20: 69,21: 55,22: 79,23: 78,24: 88,25: 79,26: 81,27: 86,28: 55,
  29: 79,30: 88,31: 90,32: 96,33: 69,34: 88},
 'gender': {0: 'female',1: 'male',2: 'male',3: 'female',4: 'female',5: 'male',
  6: 'male',7: 'male',8: 'male',9: 'female',10: 'female',11: 'female',12: 'female',
  13: 'female',14: 'male',15: 'male',16: 'male',17: 'male',18: 'male',19: 'female',
  20: 'female',21: 'female',22: 'male',23: 'male',24: 'male',25: 'male',26: 'female',
  27: 'female',28: 'male',29: 'female',30: 'male',31: 'female',32: 'female',
  33: 'male',34: 'female'}}
df=pd.DataFrame[data=dt]
df.set_index['id',inplace=True] # using id as index 

To read Excel or CSV file .

import pandas as pd 
df= pd.read_excel['D:\\my_data\\student.xlsx'] # excel file 
df= pd.read_csv['D:\\my_data\\student.csv'] # csv  file 

Here it is shown as the file path is my_data directory inside D drive. You can change the path based on file location in your system.

Using SQLAlchemy

We will collect records from our sample student table in MySQL database.
Collect SQL dump of sample student table below.
Read more on MySQL with SQLAlchemy connection. you can add path if you want the file to be created with the string [ sample is given above ]

import pandas as pd 
from sqlalchemy import create_engine
my_conn = create_engine["mysql+mysqldb://userid:pw@localhost/my_db"]
sql="SELECT * FROM student LIMIT 0,10 "
df = pd.read_sql[sql,my_conn]

Student table as Numpy array

import numpy as np
student=np.dtype[[['id','i'],['name','S20'],['class','S10'],['mark','i4'],['Gender','S10']]]
data=[[1, 'John Deo', 'Four', 75, 'female'],\
[2, 'Max Ruin', 'Three', 85, 'male'],\
[3, 'Arnold', 'Three', 55, 'male'],\
[4, 'Krish Star', 'Four', 60, 'female'],\
[5, 'John Mike', 'Four', 60, 'female'],\
[6, 'Alex John', 'Four', 55, 'male'],\
[7, 'My John Rob', 'Five', 78, 'male'],\
[8, 'Asruid', 'Five', 85, 'male'],\
[9, 'Tes Qry', 'Six', 78, 'male'],\
[10, 'Big John', 'Four', 55, 'female'],\
[11, 'Ronald', 'Six', 89, 'female'],\
[12, 'Recky', 'Six', 94, 'female'],\
[13, 'Kty', 'Seven', 88, 'female'],\
[14, 'Bigy', 'Seven', 88, 'female'],\
[15, 'Tade Row', 'Four', 88, 'male'],\
[16, 'Gimmy', 'Four', 88, 'male'],\
[17, 'Tumyu', 'Six', 54, 'male'],\
[18, 'Honny', 'Five', 75, 'male'],\
[19, 'Tinny', 'Nine', 18, 'male'],\
[20, 'Jackly', 'Nine', 65, 'female'],\
[21, 'Babby John', 'Four', 69, 'female'],\
[22, 'Reggid', 'Seven', 55, 'female'],\
[23, 'Herod', 'Eight', 79, 'male'],\
[24, 'Tiddy Now', 'Seven', 78, 'male'],\
[25, 'Giff Tow', 'Seven', 88, 'male'],\
[26, 'Crelea', 'Seven', 79, 'male'],\
[27, 'Big Nose', 'Three', 81, 'female'],\
[28, 'Rojj Base', 'Seven', 86, 'female'],\
[29, 'Tess Played', 'Seven', 55, 'male'],\
[30, 'Reppy Red', 'Six', 79, 'female'],\
[31, 'Marry Toeey', 'Four', 88, 'male'],\
[32, 'Binn Rott', 'Seven', 90, 'female'],\
[33, 'Kenn Rein', 'Six', 96, 'female'],\
[34, 'Gain Toe', 'Seven', 69, 'male'],\
[35, 'Rows Noump', 'Six', 88, 'female']]
student=np.array[data] # adding data 
print[student]

Pandas sample DataFrame creating from Excel or CSV or from MySQL or copy the dictionary with data

Exercise 1 [basic ]
Pandas Plotting graphs Filtering of Data

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