FinFeedAPI - Flat Files – Calculating Returns & Identifying Top Movers from OHLCV Data

Flat Files – Calculating Returns & Identifying Top Movers from OHLCV Data

This tutorial shows you exactly how to go from a CSV file → to analysis → to output files.

You will learn how to:

Run Python properly
Load Flat Files data
Calculate returns
Identify top gainers and losers
Save results into new files

📦 Step 0: Prepare Your Environment

✅ What you need

Your CSV file, example:

1D-20260202.csv

👉 We also have a tutorial on how to extract Flat Files here: Flat Files S3 API – Complete Guide: Authentication, Discovery, Download & Extraction

Python installed
- Check if Python is installed:

1python--version
2
3or:
4
5python3--version

Install Pandas

1pip install pandas
2
3or:
4
5pip3 install pandas

📁 Step 1: Set Up Your Working Folder

Create a folder, for example:

1flatfiles/

Put your CSV inside:

1flatfiles/
2├── D-20260202.csv

🧾 Step 2: Create Your Python Script

Inside the same folder, create a file:

1returns_analysis.py

✍️ Paste This Code (Complete Script)

1import pandas as pd
2
3# Step 1: Load the CSV file into memory (DataFrame)
4df=pd.read_csv("D-20260202.csv",delimiter=";")
5
6# Step 2: Calculate returns
7df["return"]= (df["price_close"]-df["price_open"])/df["price_open"]
8
9# Step 3: Show preview in terminal
10print("\nPreview of data with returns:")
11print(df[["exchange_symbol","price_open","price_close","return"]].head())
12
13# Step 4: Identify top gainers
14top_gainers=df.sort_values("return",ascending=False).head(5)
15
16# Step 5: Identify top losers
17top_losers=df.sort_values("return",ascending=True).head(5)
18
19# Step 6: Print results
20print("\nTop Gainers:")
21print(top_gainers[["exchange_symbol","return"]])
22
23print("\nTop Losers:")
24print(top_losers[["exchange_symbol","return"]])
25
26# Step 7: Save results to files
27df.to_csv("with_returns.csv",index=False)
28top_gainers.to_csv("top_gainers.csv",index=False)
29top_losers.to_csv("top_losers.csv",index=False)
30
31print("\n✅ Done! Files created:")
32print("- with_returns.csv")
33print("- top_gainers.csv")
34print("- top_losers.csv")

🖥️ Step 3: What You Will See

Terminal Output

1Preview of data with returns:
2SWVL  3.03 → 3.17 → 0.046
3TSM   329.44 → 329.69 → 0.0007
4...
5
6Top Gainers:
7SWVL ...
8GLL ...
9
10Top Losers:
11...

New Files Created

In your folder:

1flatfiles/
2├── D-20260202.csv
3├── returns_analysis.py
4├── with_returns.csv      ✅ (full dataset + return column)
5├── top_gainers.csv       ✅
6├── top_losers.csv        ✅

⚠️ Common Beginner Mistakes (Avoid These)

❌ Running Python code in terminal

Wrong:

1print(df.head())

Correct:

1python returns_analysis.py

❌ Forgetting delimiter

Wrong:

1pd.read_csv("file.csv")

Correct:

1pd.read_csv("file.csv",delimiter=";")

🎯 Final Takeaway

You now have a complete workflow:

1CSV file → Python (DataFrame) → Calculate → Rank → Save results