Definition
Pandas என்பது Python-ல் data analysis, data manipulation, data cleaning, tabular data processing போன்ற வேலைகள……
Pandas
Pandas என்பது Python-ல் data analysis, data manipulation, data cleaning, tabular data processing போன்ற வேலைகளை எளிதாக செய்ய பயன்படும் open-source library. Pandas முக்கியமாக labeled/tabular data உடன் வேலை செய்ய designed செய்யப்பட்டிருக்கிறத…
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89 programs 25 MCQs v4
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Simple Explanation
ஒரு Excel sheet நினைத்துக் கொ……
Simple Explanation
இது: Rows + Columns + Data Pandas இ……
Program
Example
Flow
Raw Data ↓ Pandas மூலம் Read ↓ Series / DataFrame ↓ View Data ↓ Select Data ↓ Clean Data ↓ Filter Data ↓ Anal……
Syntax
Pandas import
Explanation
pandas → Library name pd → Co……
Syntax
Create Series
Syntax
Read CSV
Why Pandas?
Pandas mainly useful for: Data analysis Data cleaning CSV processing Spreadsheet-like operations Missing data……
Installing Pandas
Terminal / Command Prompt: pi……
Important
Pandas-க்கு commonly used alias: ……
Memory Trick
Pandas → pd NumPy → np Pandas……
Main Pandas Data Structures
Pandas-ல் beginner level-க்கு……
Definition
A Series என்பது one-dimensional labeled data struct……
Program
Example
Exact integer dtype can depend on platform/configurat……
Explanation
marks = pd.Series([80, 90, 70……
Important
Pandas default indexing gener……
Series with Custom Index
Now labels: Arun Bala Kumar a……
Memory Trick
Series: Index + Value 0 → 80 ……
Definition
DataFrame என்பது two-dimensional labeled tabular data structure. Row……
Program
Example
Simple Explanation
Series: ஒரு column மட்டும். D……
Explanation
Example
Name Mark Arun 90 Bala 80 இது……
DataFrame Components
ஒரு DataFrame-க்கு முக்கியமாக……
Explanation
Example
Name Mark 0 Arun 90 1 Bala 85 2 Kumar 95 ……
Creating DataFrame from Dictionary
head()
Definition
head() DataFrame-ன் starting rows பார்……
Explanation
If DataFrame has many rows, f……
Explanation
First 3 rows.…
Memory Trick
Head = Top head() → மேலே உள்ள……
tail()
tail() DataFrame-ன் last rows பார்க்க பயன்படு……
Memory Trick
Tail = End tail() → Bottom / ……
View Full DataFrame
Program
Small DataFrame
முழு table-ஐ display செய்யும்.…
Important
Very large DataFrame இருந்தால் Pandas ……
shape
Definition
shape tells: (number of rows,……
Program
Example
Explanation
If: 3 rows 3 columns…
Memory Trick
shape = Rows × Columns struct……
size
size total number of values/e……
Explanation
Example
3 rows × 3 columns:…
ndim
Program
DataFrame normally
Because DataFrame is two-dime……
columns
Program
Column names பார்க்க
Output
Possible output
The exact representation may ……
index
Program
Row index பார்க்க
For default indexing it repre……
dtypes
Each column data type பார்க்க:…
Possible concept: Name string/object-like Age integer Ma……
info()
Definition
info() DataFrame பற்றி concise technical summary கொடுக்கிறது. d……
Explanation
df.info() இது large dataset u……
Memory Trick
info() = DataFrame health card…
describe()
Definition
describe() numerical columns-க்கு descriptive statistics ……
Simple Explanation
Suppose Marks: 80 90 70 100 describe() அவற்றின்: Cou……
TRB Point
describe() → Statistical summ……
Selecting a Column
Suppose: df contains: Name Ag……
Single column selection norma……
Important
df["Name"] → Series But: df[[……
Selecting Multiple Columns
loc
Definition
.loc[] is primarily label-based selection. It can select ……
Explanation
Syntax
df.loc[row_label] or: df.loc[……
Output
Possible output
Program
Specific cell
Memory Trick
loc = Label…
iloc
Definition
.iloc[] is primarily integer-position based……
Explanation
Syntax
df.iloc[row_position] or: df.……
Explanation
First row. Specific cell:…
Explanation
Row position: 0 Column positi……
Output
Result
Comparison
loc vs iloc
Comparison
Pandas documentation explicitly distinguishes .……
Important
Don't memorize: loc = row iloc =……
Comparison
Difference
Row Slicing with iloc
Positions: 0 1 are returned. ……
Selecting Rows and Columns
Definition
Meaning
Rows: 0, 1 Columns: 0, 1…
Filtering Data
Filtering is one of Pandas' most powerful fe……
Output concept: Name Mark Aru……
Flow
df["Mark"] > 80 produces Boolean condit……
Important
Comparison operators: < =…
Multiple Conditions
Use & for AND-like element-wi……
Use | for OR-like combination:…
Common Mistake
Wrong: df["Mark"] > 80 and df["Age"] < 21 For Series boole……
Memory Trick
Pandas conditions: & → AND | ……
Add New Column
df["Result"] = ["Pass", "Pass……
Explanation
df["Bonus"] = 5…
Explanation
Every row gets 5.…
Create Column from Existing Column
df["NewMark"] = df["Mark"] + 5 If: Mark 90……
Update a Value
Using loc: df.loc[0, "Mark"] ……
Rename Columns
Mark becomes: Score…
Drop Column
Drop Row
Reset Index
Program
After deleting/filtering rows
Pandas documentation says reset_index() res……
Sorting Data
Use: sort_values()…
Program
Example
Explanation
Ascending order. Descending:…
Explanation
Pandas sort_values() sorts by specified values a……
Program
Code
Output
Result
Memory Trick
ascending=True → Small to Lar……
Missing Data
Real datasets-ல் சில values m……
Explanation
Example
Name Mark Arun 90 Bala NaN Kumar 80 Missing data handling is an important Pandas featu……
NaN
NaN often indicates: Not a Number / missing numerical data rep……
Detect Missing Values - isna()
Output concept: False True Fa……
isnull()
df.isnull() also commonly use……
Count Missing Values
Explanation
Example
Name 0 Mark 2 Age 1…
Definition
Meaning
Mark → 2 missing Age → 1 miss……
fillna()
Definition
fillna() missing values-ஐ specified replacement value கொண்டு fill செய்ய பயன்ப……
Explanation
Example
df["Mark"] = df["Mark"].filln……
Explanation
Missing values replaced with ……
Simple Explanation
Marks: 80 NaN 100 Mean of ava……
Forward Fill
Modern pandas provides: df.ffill……
Explanation
Example
Before: 10 NaN 20 After forwa……
dropna()
dropna() removes rows/columns according to missing-……
Program
Example
Explanation
Rows with missing values remo……
Common Mistake
Don't blindly use: df.dropna() on every dataset. Why? Im……
Duplicate Data
Check duplicates: df.duplicated……
value_counts()
Definition
value_counts() counts how man……
Program
Example
Explanation
Suppose: Chennai Madurai Chen……
Memory Trick
value_counts = Frequency…
Unique Values
df["City"].unique() Returns unique……
Basic Statistical Functions
Program
Suppose
Mean: marks.mean() Median: marks.median() Minimum: marks.min……
GroupBy
Definition
groupby() same category-க்கு சேர்ந்த rows-ஐ groups ஆக ……
Explanation
df.groupby("Department") CS rows one group. Maths rows anothe……
Dry Run
CS: 90 + 80…
2 = 85 Maths: 70 + 100 2 = 85…
Memory Trick
GroupBy = Split → Apply → Com……
Aggregation
Program
Multiple calculations
Output
Possible output
Reading CSV
Definition
CSV: Comma-Separated Values Example file: Name,Mark,City Arun,90,Che……
Flow
CSV File ↓ pd.read_csv() ↓ Da……
Important
Common error on Windows: Wrong: pd.read_csv("C:\Users\Admin\Downloads\students.csv") Backslashes ……
Saving DataFrame to CSV
means DataFrame index is not ……
Reading Excel
When the required Excel engin……
Program
Save
String Operations
Suppose: df["Name"] contains names. Convert to ……
Contains: df["Name"].str.cont……
Explanation
Before: Arun Bala After: ARUN……
Replace Values
Mapping Values
Program
Example
Explanation
df["Code"] = df["Result"].map……
Apply a Function
Program
Example
Explanation
df["NewMark"] = df["Mark"].apply(add_bonus) For si……
Concatenating DataFrames
Pandas provides facilities for combining Series……
Program
Example
Simple Explanation
df1: Arun Bala df2: Kumar Rav……
Merge
Suppose: Student table: ID Name 1 Arun 2 Bala Mark……
Output
Result
Set Index
Before: 0 Arun 1 Bala After: ……
Reset Index
Returns index back into ordinar……
Complete Student Example
Explanation
df["Mark"] selects Mark column. df["Mark"] > 80……
Explanation
Create Result Column df["Resu……
Output
Possible result
Explanation
Calculation: 90 + 75 + 95 + 80…
4 340 / 4 = 85…
Pandas + NumPy Relationship
NumPy: Main focus: Numerical A……
Comparison
NumPy vs Pandas
Memory Trick
NumPy = Numbers Pandas = Tabl……
Important
Series vs DataFrame…
Remember
df["Mark"] → Series df[["Mark……
Important
loc vs iloc loc → LABEL iloc → INTEGER ……
Important
Pandas Master Workflow…
Remember
READ ↓ VIEW ↓ CHECK ↓ CLEAN ↓ SELECT ↓ FILTER ↓ ANALYZE ↓ GROUP ↓ SAV……
Common Mistake
Error 1
Pandas alias mistake Correct: import pandas as ……
Common Mistake
Error 2
loc and iloc confuse செய்வது ……
Common Mistake
Error 3
Column name case If column is: Mark Wrong……
Common Mistake
Error 4
Single vs Double Brackets df[……
Common Mistake
Error 5
Filtering without parentheses Wrong: df[ df["Mark……
Common Mistake
Error 6
head without brackets Wrong if ……
Common Mistake
Error 7
Missing file pd.read_csv("student.csv") File not f……
Common Mistake
Error 8
Missing values ignored Don't immediately perform calculations without checking data quality. First: d……
Memory Trick
Pandas Master Memory S D H T L I F G S → Serie……
Memory Trick
Cleaning Memory I F D D I → isn……
Memory Trick
Dataset Inspection…
Remember
HEAD SHAPE INFO DESCRIBE First data……
TRB Point
TRB Point 1
Pandas is a Python library fo……
TRB Point
TRB Point 2
Common Pandas alias: pd…
TRB Point
TRB Point 3
Two major structures: Series ……
TRB Point
TRB Point 4
Series is one-dimensional lab……
TRB Point
TRB Point 5
DataFrame is two-dimensional tab……
TRB Point
TRB Point 6
Create DataFrame: pd.DataFram……
TRB Point
TRB Point 7
Read CSV: pd.read_csv()…
TRB Point
TRB Point 8
First rows: head()…
TRB Point
TRB Point 9
Last rows: tail()…
TRB Point
TRB Point 10
shape returns: (rows, columns)…
TRB Point
TRB Point 11
loc is primarily label based.…
TRB Point
TRB Point 12
iloc is primarily integer-pos……
TRB Point
TRB Point 13
Missing value detection: isna……
TRB Point
TRB Point 14
Missing values can be filled ……
TRB Point
TRB Point 15
Missing-data rows can be remo……
TRB Point
TRB Point 16
Duplicate rows: duplicated()…
TRB Point
TRB Point 17
Remove duplicates: drop_dupli……
TRB Point
TRB Point 18
Sort: sort_values()…
TRB Point
TRB Point 19
Group data: groupby()…
TRB Point
TRB Point 20
Frequency: value_counts()…
TRB Point
TRB Point 21
Statistical summary: describe……
TRB Point
TRB Point 22
Data structure summary: info()…
TRB Point
TRB Point 23
Save CSV: to_csv()…
TRB Point
TRB Point 24
df["column"] normally returns……
TRB Point
TRB Point 25
df[["column"]] returns DataFr……
Interview Point
Question 1
What is Pandas? Answer Pandas is an open-source Python librar……
Interview Point
Question 2
What is a Series? Answer A Series is a one-dime……
Interview Point
Question 3
What is a DataFrame? Answer A DataFrame is a two-dimensional la……
Interview Point
Question 4
What is the difference between loc and iloc? Answe……
Interview Point
Question 5
How do you detect missing values? Answer Common methods include: ……
Interview Point
Question 6
How can missing values be fil……
Explanation
Example
df["Mark"] = df["Mark"].filln……
Interview Point
Question 7
What is groupby()? Answer groupby() groups rows according to one or mo……
Interview Point
Question 8
What is the difference between Pandas and NumPy? Answer NumPy focuses mainly on efficient multidimensio……
MCQ
Pandas is mainly used for:…
MCQ
Common alias for Pandas:…
MCQ
Which creates a DataFrame?…
MCQ
A Pandas Series is mainly:…
MCQ
A DataFrame is mainly:…
MCQ
Which reads CSV?…
MCQ
Which shows first rows?…
MCQ
Which shows last rows?…
MCQ
What does shape represent?…
MCQ
Which is label-based?…
MCQ
Which is integer-position bas……
MCQ
Which detects missing values?…
MCQ
Which fills missing values?…
MCQ
Which removes missing-data ro……
MCQ
What does this generally retu……
MCQ
What does this return? df[["M……
MCQ
Which sorts rows by column va……
MCQ
Which groups rows according t……
MCQ
Which counts frequency of eac……
MCQ
Which gives numerical statist……
MCQ
What is the result conceptual……
MCQ
Which writes DataFrame to CSV?…
MCQ
ascending=False means:…
MCQ
Which can combine DataFrames ……
MCQ
Which is suitable for databas……
Practice
Practice 1
Create a Series: 10 20 30 40 Answer: ……
Practice
Practice 2
Create DataFrame: Name Mark Arun 90 Bala 80 Kumar 95 Answer: import pan……
Practice
Practice 3
Print first two rows: print(d……
Practice
Practice 4
Print last two rows: print(df……
Practice
Practice 5
Find DataFrame shape: print(d……
Practice
Practice 6
Select only Name: print(df["N……
Practice
Practice 7
Select Name and Mark: print(d……
Practice
Practice 8
Find first row using iloc: pr……
Practice
Practice 9
Find first student's Mark: pr……
Practice
Practice 10
Filter Mark > 80: print( df[d……
Practice
Practice 11
Add Bonus column: df["BonusMa……
Practice
Practice 12
Find average mark: print(df["……
Practice
Practice 13
Find highest mark: print(df["……
Practice
Practice 14
Sort highest to lowest: print……
Practice
Practice 15
Check missing values: print(d……
Practice
Practice 16
Fill missing Marks with zero:……
Practice
Practice 17
Read CSV: df = pd.read_csv("s……
Practice
Practice 18
Save result: df.to_csv( "resu……
Practice
Practice 19
Count students from each city……
Practice
Practice 20
Find department average: prin……
Summary
Pandas is used for data analysis and manipulation. Common Pandas alias is pd. Series is a one-dimensional lab……
Quick Revision
Pandas → Data Analysis Alias → pd 1D → Series 2D → DataFrame Create Series → pd.Series() Create DataFrame → p……
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