Time series
A time series is a list of measurements of the same thing taken in order, every day, month or year, like daily sales or monthly inflation.
Select any words here to ask your Maestro about them.
A promotion pushed orders to their highest day on day 21. The dashboard draws the 7-day average (each day and the 6 before it). On what day does that line peak?
What makes it different: order matters. Each value is usually related to the ones before it, so you can't shuffle the rows or treat them as independent. It's almost always drawn as a line chart.
Its parts: a trend (whether it rises or falls over the years), seasonality (patterns that repeat, like Saturdays or December) and noise. To see the trend, you smooth it with a moving average, the mean of the last few days.
Where it shows up: daily sales, hourly visits, monthly inflation, stock prices. In pandas you work with resample and rolling, and to forecast you use models like ARIMA or Prophet.
How it's used
In pandas
orders.py
- weekly = df.resample("W", on="date")["orders"].sum()Groups the days into weeks.
- df["avg_7"] = df["orders"].rolling(7).mean()The average of each day and the 6 before.
- marked: df["avg_c"] = df["orders"].rolling(7, center=True).mean()Centered: 3 days before and 3 after.
When to look closer
Same day last year
Against last year
- Saturday, November 7, 2026 against November 7, 2025
You compare sales on Saturday, November 7, 2026 with November 7, 2025. What can go wrong?
Ask your Maestro about Time series
It answers from the free course page closest to this word, the way it answers while you study.
You: What does "Time series" mean, in plain words?
Your Maestro: I'll explain it with a case of yours: it sticks better than a definition. Which number at work do you check every day or every week?
Asking about: Answers from the page "How do I group sales by month and by quarter?"
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Related terms
- Line chart
A line chart joins points in order, almost always over time, to show how a number changes: whether it rises, falls or repeats every season.
- Percent change
Percent change says how much a number moved relative to where it started: (new − old) ÷ old × 100. If sales go from $80K to $100K, they're up 25%.
- Mean (average)
To find the mean (the average), add up all the values and divide by how many there are: 15, 7, 8, 13 and 7 add up to 50, and 50 ÷ 5 = 10.
- pandas
pandas is a Python package for working with tables of data, called DataFrames: loading them, filtering rows, picking columns and summarizing them.