Python lesson

Picking rows and saving

6 orders, saved to picked.csv. index=False leaves out the row numbers, so the file opens cleanly in Excel.

About 5–10 minutes · no sign-up needed

Example

.isin keeps the rows that match any value in a list, and .to_csv saves the result as a file:

picked = df[df["Product"].isin(["Earbuds", "Charger"])]
picked.to_csv("picked.csv", index=False)
picked

Output:

Order Day Store Product Qty Revenue
0 O101 Mon Lagos Earbuds 2 70
1 O102 Mon Abuja Charger 1 15
3 O104 Wed Lagos Earbuds 1 35
4 O105 Wed Abuja Earbuds 4 140
5 O106 Thu Lagos Charger 2 30
7 O108 Fri Lagos Earbuds 3 105

Key points

.isin(["Earbuds", "Charger"])Keep rows whose value is in the list.

.str.contains("Ear")Keep rows whose text includes "Ear". Capitals matter.

.loc[test, ["Store", "Revenue"]]Rows by a test, then only the columns you want.

.to_csv("file.csv", index=False)Save it as a file. index=False leaves out the row numbers.

Pick with .isin, .str.contains or .loc, then save with .to_csv("file.csv", index=False).

Practice

Try each one in your head first, then open the answer.

1. Build a line that keeps only the Earbuds and Charger orders.

df[df["Product"].isin(["Earbuds", "Charger"])]

2. Build a line that shows the Store and Revenue of every order over 50.

df.loc[df["Revenue"] > 50, ["Store", "Revenue"]]

3. Show only the Earbuds and Phone case orders.

df[df["Product"].isin(["Earbuds", "Phone case"])]

4. Show the orders whose product contains the word case.

df[df["Product"].str.contains("case")]

5. Save the Lagos orders as lagos.csv for the store manager, without the row numbers.

lagos = df[df["Store"] == "Lagos"]
lagos.to_csv("lagos.csv", index=False)

Learn it by doing. This lesson is a short hands-on level on Bampaa: see it work, then build and write it yourself, with instant feedback.

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About 5–10 minutes · no sign-up needed