Data Science · मराठी आवृत्ती
22.6 सामान्य export चुका
या course चे सर्व chapters (py + ch)
- How to Use This Free Data Science Course
- How to Install Python, Jupyter Notebook and VS Code for Data Science (Windows and Mac)
- Python Variables and Data Types Explained for Beginners (int, float, str, bool)
- Python Strings Tutorial: Slicing, f-strings and String Methods with Examples
- Python Lists, Tuples, Dictionaries and Sets Explained with Examples
- Python if, elif and else Statements with Real Examples for Beginners
- Python for Loops and while Loops Explained with Examples (range, break, continue)
- Python Functions Tutorial: def, return, Arguments and lambda with Examples
- Python Errors and Exceptions: How to Use try, except, else and finally
- How to Read and Write CSV, JSON and Text Files in Python (with open and with)
- Python Modules, pip and Virtual Environments (venv) Explained for Beginners
- Python Classes and Objects for Beginners: OOP Basics with Simple Examples
- NumPy Tutorial for Beginners: Arrays, Maths and Filtering in Python
- Python Mini Projects for Beginners: 5 Practice Projects Before Learning pandas
- Data Science vs Data Analytics Tutorial
- Python Jupyter Setup for Data Science
- Python Basics for Data Science Tutorial
- NumPy Essentials for Data Science Tutorial
- pandas DataFrames and Series Tutorial
- Filter and Sort Data in pandas Tutorial
- pandas GroupBy and Aggregations Tutorial
- Merge and Concat Data in pandas Tutorial
- Data Cleaning in pandas A–Z Tutorial
- Dates and Text in pandas – Free Tutorial
- Reshape Data: melt and pivot_table
- Exploratory Data Analysis in Python
- matplotlib Visualization Tutorial – Free
- seaborn Visualization Tutorial – Free
- Chart Choice and Data Storytelling
- Data Science Project: Blinkit Maharashtra
- Data Science Practice Exercises
- Data Science Interview Questions
- pandas matplotlib seaborn Cheat Sheet
- Data Science Glossary – Free Tutorial
- Stats for Data Work Mean Median IQR
- Export CSV Excel PNG from pandas Tutorial
- Common pandas Mistakes and Fixes Tutorial
- Load SQL Query Results into pandas DataFrame – Free Tutorial
- How to Rank and Running Totals in pandas
- How to Read APIs, JSON and Zipped CSVs into pandas
- How to Use Git with Jupyter Notebooks for Data Projects
- How to Merge and Join Tables in pandas for Blinkit Data
- What Is Machine Learning Simple Explanation
- Machine Learning Workflow Step by Step
- Train Test Split in Machine Learning sklearn
- Features and Labels in Machine Learning
- Linear Regression in Python with sklearn
- Classification with Logistic Regression in Python
- Decision Trees and Random Forests in Python
- K-Means Clustering in Python for Beginners
- How to Check If Your ML Model Is Good
- Overfitting and Underfitting in Machine Learning
- End-to-End ML Project India Dataset
- Data Preprocessing for ML: Impute Scale Encode
- What Is a Neural Network Simple Explanation
- Activation Loss Gradient Descent Plain English
- Backpropagation Intuition No Heavy Maths
- Install PyTorch and First Tensors
- Your First Neural Network in PyTorch
- Deep Learning vs Classical ML When to Use Which
- Convolutional Neural Networks CNNs for Images
- Small CNN Image Project in PyTorch
- What Transformers Are Text and Sequences
- Tiny Text Classifier Transformer Intro PyTorch
- What Is Natural Language Processing NLP
- Text Cleaning and TF-IDF in Python sklearn
- Sentiment Analysis Project in Python TF-IDF
- NLP vs ChatGPT Classical NLP and Generative AI
हे का शिकायचं?
चुकीचा encoding, index column, किंवा जुनी file overwrite — यामुळे trust तुटतो.
हे काय आहे?
Checklist: index=False, UTF-8, स्पष्ट filename, outputs/ path, open-and-verify.
कसं करायचं?
Step 1. CSV Excel मध्ये उघडून गड़बड़ अक्षरे तपासा.
Step 2. पहिला column अनोळखी index तर index=False.
Step 3. जास्त मोठी sheet नाही ना.
Step 4. जुनी PNG overwrite झाली का पाहा.
उदाहरणं: copy करा आणि चालवा
उदाहरण A — Comma trap.
import pandas as pd
ugly = pd.DataFrame({"amount": ["1,299", "90", "2,499"]})
# Wrong: export as-is — Excel may treat as text or split columns
ugly.to_csv("outputs/bad_amounts.csv", index=False)
fixed = ugly.copy()
fixed["amount"] = (
fixed["amount"].astype(str).str.replace(",", "", regex=False).astype(float)
)
fixed.to_csv("outputs/good_amounts.csv", index=False)
print(pd.read_csv("outputs/good_amounts.csv")["amount"].sum()) # 3888.0
उदाहरण B — Index accident.
s = df.groupby("city")["amount"].sum()
s.to_csv("outputs/with_index_mystery.csv") # index becomes a column — OK if named
s.to_csv("outputs/with_index_false.csv", index=False) # city names LOST — bad
s.rename_axis("city").reset_index(name="gmv").to_csv(
"outputs/city_gmv.csv", index=False
)
उदाहरण C — Encoding peek.
text = pd.DataFrame({"city": ["Pune", "Sambhaji Nagar"], "note": ["ok", "rain delay"]})
text.to_csv("outputs/notes_utf8.csv", index=False, encoding="utf-8")
# Round-trip
print(pd.read_csv("outputs/notes_utf8.csv", encoding="utf-8"))
If a partner only uses Excel on older Windows and complains, offer utf-8-sig and keep the utf-8 original in outputs/.