BizGapMap

Home / Coffee shops & beverage bars / Maryland / Charles County, MD

Charles County, MD — Coffee shops Saturation

How many coffee shops exist per person present — residents plus daytime workers — by ZIP code, compared with the U.S. average. Establishment data: Census ZBP 2023. Population: ACS 2024 5-year. 22 ZIP codes analyzed.

Includes: Coffee shops · Espresso bars · Boba / bubble tea shops · Juice & smoothie bars · Ice cream & frozen yogurt shops. Counted together because official statistics use one 722515 code.

Measured density: Range spans bands — 0.40× the U.S. rate (between 0.40× and 1.31× once withheld ZIP cells are counted)

Why a range: Census does not publish a ZIP-by-industry count when that ZIP has 0–2 businesses. 19 ZIP cells in this county are withheld, 18 of them with residents. Each could hold 0, 1, or 2 businesses: counting them all as 0 gives the low end, counting them all as 2 gives the high end — the data cannot say where the truth sits. The density range uses only the populated cells, since ZIPs without residents are excluded from per-person rates. How ranges work

Range spans the U.S. rate   Charles County coffee shops — 40–131% of the U.S. rate

16 coffee shops are counted in Charles County — 0.9 per 10,000 people present (residents + daytime workers), 40% of the U.S. rate of 2.1.

On the comparable ZIP set (ZIPs with a published count in every year), the total has risen 14% between 2015 and 2023 (14 → 16). That set is smaller than today's county total. 2020–2021 were pandemic-distorted, and Census rounds counts, so small moves are within noise.

Measured supply density is highest in 20646 (La Plata), 20603 (Waldorf), 20601 (Waldorf) — well above the national rate. On measured density alone, the lowest-density residential ZIPs with a published count are 20601 (Waldorf), 20603 (Waldorf), 20646 (La Plata).

BLS QCEW puts the latest county-wide count (2026 Q1) at 22 establishments, the freshest available signal.

Measured density: Charles County sits at 40% of the U.S. rate for coffee shops. 18 ZIPs with population have no published count (each 0–2 businesses), so the true per-capita rate is between 40% and 131% of the U.S. rate. Why. The highest measured density is in 20646 and 20603; the lowest measured density is in 20601 and 20603.

This is a supply-side read: it counts existing coffee shops and the people present, not foot traffic, income, rent, or whether locals want more. Treat low density as a question to check, not an answer.

Coffee shops
16–54
published count; upper bound counts each withheld ZIP cell as 2 (19 cells) (2023)
Per 10,000 present
0.9
residents + daytime workers
U.S. average
2.1
per 10,000 present
County index
0.40×
vs. U.S.
Latest quarter (QCEW)
22
2026 Q1 — county total
Residents
170,349
21 ZIPs with data
Workers
35,482
jobs located in county

Is the area growing?

Population
174,478
Census PEP, July 1 2024
Change since 2020
+4.7%
+7,786 people
Net migration 2024
+2,080
international +588, domestic +1,492
Jobs located here
36,003
LODES 2022, −3.5% since 2019

Charles County had an estimated 174,478 residents on July 1, 2024 — 4.7% more than in 2020 (+7,786). In the latest year it gained 2,210 people: births minus deaths +147, international migration +588, domestic migration +1,492. Components are published separately and may not sum exactly.

36,003 jobs were located in the county in 2022 (−3.5% since 2019), and 75,788 employed residents lived there (−0.3% since 2019). LODES counts wage and salary jobs covered by unemployment insurance plus federal jobs; it excludes the self-employed and military, and counts jobs rather than unique people. 2019→2022 spans the pandemic, so read it as one change, not a trend.

Population and migration say whether the customer base is growing. They do not say whether people want another business of this type. Definitions and limits →  ·  Full county detail →

ZIP gaining residents
2015–19 → 2020–24
Change
20695 White Plains
+102.8%
ZIP losing residents
2015–19 → 2020–24
Change

No ZIP had a statistically significant decrease.

ACS 5-year estimates for 2015–2019 and 2020–2024. Only ZIPs with at least 2,000 residents in both windows and a change larger than the survey margin of error (90%) are listed — small ZIPs move a lot on paper without a real signal.

Nonemployer businesses (no paid employees)

Nonemployer businesses
4
no paid employees (2024)
Receipts
$12K
published gross receipts
Receipts per business
$3K
gross, not profit

Census Nonemployer Statistics counts businesses with no paid employees — a separate universe from the employer establishments counted above; a business is in one or the other, never both. They are not storefronts by definition: many are home-based, mobile, or part-time.

We show them beside the density index, not inside it. In categories such as nail and beauty salons, child care, and pet care, one-person businesses can outnumber employer establishments, so the employer-only count understates how many businesses exist. That is not evidence of higher demand.

Receipts are gross revenue reported for these businesses — not profit, and not the size of the local market. Census publishes this only at county level, so it is not shown on the ZIP map. See methodology.

Saturation map

Each ZIP area is shaded by its density of this business type per person present (residents + workers) vs. the U.S. average. Click any ZIP to zoom to its boundary, see its numbers, and switch to aerial imagery. Individual mapped shops appear as dots at street level — Show locations zooms you in to them (scroll or double-click to zoom).

Basemap:
Under 50% 50–100% 100–150% 150–250% 250%+ 0–2 (not published) / no data ZIP total (dot size) Mapped shop (OpenStreetMap, street level)

Map data © OpenStreetMap contributors, tiles by OpenFreeMap.

White dots are ZIP totals from the official Census count — the bigger the dot, the more coffee shops in that ZIP. They are aggregated, not individual shops. Turquoise dots are individual locations mapped in OpenStreetMap, shown only at street level; they are crowd-sourced and indicative, may be incomplete, and do not equal the official counts. Only the official ZIP totals feed the saturation index.

Market trend — up 14% since 2015

Number of coffee shops in Charles County across 2015–2023, on a consistent set of ZIP codes present in every year — so changes are real, not ZIP-boundary artifacts. 2015/2018 are pre-pandemic baselines; 2020/2021 are COVID-distorted.

14
2015
16
2018
17
2020
19
2021
20
2022
16
2023

Highest measured density

ZIP
vs. U.S. average
Index
20646 La Plata
113%
20603 Waldorf
95%
20601 Waldorf
47%

Lowest measured density

ZIP
vs. U.S. average
Index
20601 Waldorf
47%
20603 Waldorf
95%
20646 La Plata
113%
Low measured density is not evidence of opportunity. A ZIP with few coffee shops may simply lack foot traffic, retail space, or demand. We rank only residential and mixed ZIPs here; employment hubs and visitor destinations are listed separately below. ZIPs where Census did not publish a count (0–2 businesses) are not ranked: they may be the least served of all, but the data cannot tell 0 from 1 or 2. Verify those locally.

All ZIP codes

Click a column header to sort. Index = coffee shops per 10,000 people present (residents + 0.5×workers) ÷ the U.S. average. 100% = exactly average.

ZIPNeighborhood ResidentsWorkersCoffee shops Per 10kIndexStatus
20646La Plata 21,4007,759 6 2.4 113% Above average
20603Waldorf 31,8446,625 7 2.0 95% Below average
20601Waldorf 26,9457,209 3 1.0 47% Far below average
20602Waldorf 28,3315,235 0–2 — — Not published
20604Waldorf —148 0–2 — — Not published
20611Bel Alton 1,219167 0–2 — — Not published
20612Benedict 1486 0–2 — — Not published
20616Bryans Road 8,057669 0–2 — — Not published
20617Bryantown 33472 0–2 — — Not published
20622Charlotte Hall 5,1852,295 0–2 — — Not published
20625Cobb Island 84975 0–2 — — Not published
20632Faulkner 48581 0–2 — — Not published
20637Hughesville 6,1331,048 0–2 — — Not published
20640Indian Head 10,685494 0–2 — — Not published
20645Issue 81461 0–2 — — Not published
20658Marbury 86694 0–2 — — Not published
20662Nanjemoy 2,12969 0–2 — — Not published
20664Newburg 3,138288 0–2 — — Not published
20675Pomfret 1,796106 0–2 — — Not published
20677Port Tobacco 2,088208 0–2 — — Not published
20693Welcome 1,49652 0–2 — — Not published
20695White Plains 16,4072,869 0–2 — — Not published

Scroll the table sideways to see all columns.

Find an actual space in La Plata

The numbers above tell you how the market looks. To find a specific storefront, these marketplaces list available retail space for lease.

LoopNet
Largest commercial marketplace
Browse La Plata retail space →
Crexi
Free listings + market data
Browse La Plata retail space →
CityFeet
Retail space for lease
Browse La Plata retail space →

Open vacancy data (actual empty units) is only published by some cities; where it exists we show it directly. Listings above are third-party.

Census withholds some ZIP-by-industry cells to protect small businesses. 0–2 means the cell was not published (Census publishes industry counts only at 3+ per ZIP), so the ZIP is left unranked rather than counted as zero. ~ means the count is estimated from the broader industry group and can be off by a business or two.

Follow Charles County and coffee shops

When a data vintage changes or a section of this report is revised, we post it to a public update feed. No email address, no account, no tracking — and nothing is sent unless something actually changed.

Subscribe to updates (RSS) How these numbers are built →

Methodology & sources

Establishments. U.S. Census ZIP Code Business Patterns (ZBP 2023), NAICS 722515 — snack & non-alcoholic beverage bars (incl. coffee shops). Counts establishments with paid employees. ZBP is published annually with a ~2-year lag.

Fresh county signal. BLS QCEW (quarterly) is newer than ZBP — 2026 Q1 shows 22 establishments county-wide for this industry. It cannot be broken down by ZIP.

Population. U.S. Census American Community Survey 2024 5-year ZCTA population (table B01003). Workers are the ZIP's total employment from the same 2023 ZBP file.

Demand ("people present"). Demand comes from residents and daytime workers: residents + 0.5 × workers. This is the single documented assumption in the model and can be tuned.

Index. index = (ZIP establishments ÷ ZIP demand × 10,000) ÷ the U.S. average for this industry (2.10 per 10,000 present). It is a supply-side density measure; it does not capture income, rent, tourism, or whether locals actually want more.

Read the full methodology →  ·  Data sources & vintages →

BizGapMap — free, no-login small-business saturation reports for major U.S. counties. Built entirely from public U.S. Census, BLS, and IRS data (ZBP 2023, ACS 2024 5-year, PEP 2024, LODES, QCEW, IRS SOI). No forecasts, no revenue guesses — withheld cells are marked, and the few derived counts are labelled as estimates.