Data analysis

 Here is a clear, interview-focused list of IMPORTANT Pandas library functions & methods for Data Analysis and Data Cleaning.

These are the exact ones interviewers expect you to know — not everything.

You can learn + revise this in 1–2 hours.

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🐼 PANDAS IMPORTANT FUNCTIONS & METHODS (INTERVIEW READY)

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✅ 1. Reading & Writing Data (VERY IMPORTANT)

pd.read_csv()

pd.read_excel()

pd.read_json()

df.to_csv()

df.to_excel()

Use: Load and save datasets

Interview Tip: Almost every data project starts with read_csv().

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✅ 2. Basic Data Inspection (FIRST STEP IN ANALYSIS)

df.head()

df.tail()

df.info()

df.shape

df.columns

df.dtypes

Use:

Understand data structure

Check rows, columns, data types

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✅ 3. Summary & Statistics (VERY COMMON QUESTIONS)

df.describe()

df.mean()

df.median()

df.mode()

df.min()

df.max()

df.std()

Use:

Understand distribution

Detect anomalies

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✅ 4. Handling Missing Values (EXTREMELY IMPORTANT)

df.isnull()

df.isnull().sum()

df.notnull()

df.dropna()

df.fillna()

Examples:

df.dropna()

df['age'].fillna(df['age'].mean(), inplace=True)

Interview Tip: Always explain why you choose mean/median.

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✅ 5. Removing Duplicates

df.duplicated()

df.drop_duplicates()

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✅ 6. Selecting Data (FILTERING)

df['column']

df[['col1', 'col2']]

df.loc[]

df.iloc[]

Examples:

df.loc[df['age'] > 25]

df.iloc[0:5]

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✅ 7. Sorting Data

df.sort_values()

df.sort_index()

Example:

df.sort_values(by='salary', ascending=False)

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✅ 8. Renaming Columns

df.rename()

df.columns = []

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✅ 9. Data Type Conversion

df.astype()

pd.to_datetime()

Example:

df['date'] = pd.to_datetime(df['date'])

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✅ 10. Grouping & Aggregation (VERY IMPORTANT)

df.groupby()

Example:

df.groupby('department')['salary'].mean()

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✅ 11. Applying Functions

df.apply()

df.map()

df.applymap()

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✅ 12. Merging & Joining Data

pd.merge()

df.join()

pd.concat()

Example:

pd.merge(df1, df2, on='id', how='inner')

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✅ 13. String Operations (VERY USEFUL)

df['name'].str.lower()

df['email'].str.contains()

df['text'].str.replace()

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✅ 14. Index Operations

df.set_index()

df.reset_index()

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✅ 15. Value Counts (VERY COMMON)

df['column'].value_counts()

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⭐ MOST IMPORTANT FOR INTERVIEWS (MUST REMEMBER)

If you remember ONLY these, it’s enough:

read_csv

head

info

describe

isnull

fillna

dropna

drop_duplicates

groupby

sort_values

merge

value_counts

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🎯 1-Minute Interview Answer (MEMORIZE THIS)

> “In Pandas, I usually start with read_csv() to load data, use head(), info() and describe() for understanding the dataset. For cleaning, I use isnull(), fillna(), and drop_duplicates(). For analysis, I use groupby(), sorting, and aggregation functions. Finally, I export clean data using to_csv().”

This answer sounds confident and professional.

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🔥 If you want next:

Pandas interview questions

Mini Pandas project

Cheat-sheet PDF

SQL vs Pandas comparison

Just tell me 👍