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Descrizione
English: This chart depicts the growth of Bluesky, a social network. Data spans May 2023 until January 2024, and shows an increase from 55k to 3.0M users. The chart uses population data from Bluesky API requests rendered into SVG 1.1 using Matplotlib 3.7.2 via Python 3.11.5.
Disclaimer
InfoField
English: Due to the loss of vqv.app on 2023-11-07, a total of 68 Internet Archive captures across ~70 days from vqv.app/stats/chart, bsky.jazco.dev/stats, and twexit.nl were individually sorted by timestamp, then used to approximate the daily population totals as they would have appeared at the end of each day via linear interpolation. A spreadsheet containing all citations to the relevant Internet Archive captures are available here: Google Sheets. While efforts were made to ensure accuracy, some degree of estimation is inherent in the interpolation process.
Data
Fonte Bluesky API. Daily population data until 2023-11-07 from https://vqv.app/stats/chart [collegamento interrotto]; Internet Archive for snapshots of user totals from https://bsky.jazco.dev/stats and https://twexit.nl/.
Autore VintageNebula, with data gathered by Eddie Silva, Pedro Borracha, Jaz, and Adraianus
Altre versioni
Questo file rimpiazza File:BlueSky user growth.png. Si raccomanda di usare questo file in luogo dell'altro. Si noti che la cancellazione di un'immagine rimpiazzata è soggetta a consenso.

Bahasa Indonesia ∙ davvisámegiella ∙ Deutsch ∙ English ∙ español ∙ français ∙ italiano ∙ magyar ∙ Nederlands ∙ polski ∙ svenska ∙ македонски ∙ മലയാളം ∙ português do Brasil ∙ русский ∙ slovenščina ∙ 日本語 ∙ 中文（简体） ∙ 中文（繁體） ∙ farsi ∙ +/−

minor quality
Questa è una immagine ritoccata, il che significa che è stata modificata digitalmente dalla sua versione originale. Modifiche: Generated with MatPlotLib with updated data and vectorized from source data. La versione originale può essere vista qui: BlueSky user growth.png. Le modifiche sono di VintageNebula.

SVG sviluppo
InfoField
W3C grn 
Il codice sorgente di questo file SVG è valido.
Created with Matplotlib-logo 
Questo grafico in grafica vettoriale è stato creato con Matplotlib.
Codice sorgente
InfoField

Python code

Created using Matplotlib 3.7.2 via Python 3.11.5 
# Bluesky Registered Users v1.3 
# Created for Wikimedia Commons; last edited: 2024-01-15

import matplotlib.pyplot as plt
import matplotlib.dates as mdates
from matplotlib.ticker import FixedLocator
from datetime import datetime

'''
The 'data_array' variable holds the population dataset. Each day and value is paired in a list of strings,
formatted as "YYYY-MM-DD, ######", where YYYY-MM-DD is the ISO 8601 date, and ###### is the number of 
existing users at the end of the day listed. Note that values after 2023-11-07 were calculated using
linear interpolation using website captures on the Internet Archive, and are rounded to the nearest 500.
'''
data_array = [
    "2023-05-02, 55570", "2023-05-03, 58119", "2023-05-04, 60909", "2023-05-05, 63362",
    "2023-05-06, 65035", "2023-05-07, 66194", "2023-05-08, 67477", "2023-05-09, 69053",
    "2023-05-10, 70898", "2023-05-11, 72458", "2023-05-12, 74236", "2023-05-13, 76326",
    "2023-05-14, 77472", "2023-05-15, 78972", "2023-05-16, 80328", "2023-05-17, 81682",
    "2023-05-18, 83411", "2023-05-19, 84718", "2023-05-20, 85805", "2023-05-21, 86699",
    "2023-05-22, 87761", "2023-05-23, 89034", "2023-05-24, 90565", "2023-05-25, 92559",
    "2023-05-26, 94625", "2023-05-27, 96395", "2023-05-28, 97927", "2023-05-29, 99408",
    "2023-05-30, 101215", "2023-05-31, 102578", "2023-06-01, 103919", "2023-06-02, 105437",
    "2023-06-03, 106591", "2023-06-04, 107638", "2023-06-05, 108875", "2023-06-06, 110169",
    "2023-06-07, 111989", "2023-06-08, 113673", "2023-06-09, 115868", "2023-06-10, 118019",
    "2023-06-11, 120206", "2023-06-12, 122911", "2023-06-13, 124731", "2023-06-14, 128350",
    "2023-06-15, 131274", "2023-06-16, 133937", "2023-06-17, 136152", "2023-06-18, 137423",
    "2023-06-19, 138780", "2023-06-20, 140016", "2023-06-21, 143093", "2023-06-22, 153451",
    "2023-06-23, 157707", "2023-06-24, 159933", "2023-06-25, 161913", "2023-06-26, 164419",
    "2023-06-27, 169343", "2023-06-28, 174342", "2023-06-29, 179043", "2023-06-30, 184094",
    "2023-07-01, 203365", "2023-07-02, 222026", "2023-07-03, 240687", "2023-07-04, 254189",
    "2023-07-05, 262135", "2023-07-06, 271292", "2023-07-07, 278898", "2023-07-08, 284516",
    "2023-07-09, 287745", "2023-07-10, 291393", "2023-07-11, 294869", "2023-07-12, 299667",
    "2023-07-13, 304946", "2023-07-14, 309949", "2023-07-15, 313683", "2023-07-16, 317209",
    "2023-07-17, 321258", "2023-07-18, 324959", "2023-07-19, 328269", "2023-07-20, 331240",
    "2023-07-21, 335652", "2023-07-22, 340658", "2023-07-23, 347321", "2023-07-24, 370048",
    "2023-07-25, 386014", "2023-07-26, 394662", "2023-07-27, 404693", "2023-07-28, 414773",
    "2023-07-29, 423934", "2023-07-30, 433895", "2023-07-31, 442390", "2023-08-01, 450486",
    "2023-08-02, 458146", "2023-08-03, 472748", "2023-08-04, 487476", "2023-08-05, 499582",
    "2023-08-06, 511605", "2023-08-07, 525141", "2023-08-08, 535769", "2023-08-09, 543286",
    "2023-08-10, 550163", "2023-08-11, 556915", "2023-08-12, 563776", "2023-08-13, 571517",
    "2023-08-14, 581620", "2023-08-15, 591309", "2023-08-16, 601562", "2023-08-17, 611424",
    "2023-08-18, 639033", "2023-08-19, 659173", "2023-08-20, 670671", "2023-08-21, 682208",
    "2023-08-22, 692512", "2023-08-23, 703097", "2023-08-24, 723279", "2023-08-25, 742913",
    "2023-08-26, 758806", "2023-08-27, 768190", "2023-08-28, 777341", "2023-08-29, 788438",
    "2023-08-30, 807753", "2023-08-31, 826957", "2023-09-01, 845340", "2023-09-02, 855268",
    "2023-09-03, 865253", "2023-09-04, 875942", "2023-09-05, 887544", "2023-09-06, 898496",
    "2023-09-07, 913032", "2023-09-08, 933157", "2023-09-09, 952217", "2023-09-10, 968247",
    "2023-09-11, 980472", "2023-09-12, 1001758", "2023-09-13, 1017594", "2023-09-14, 1028614",
    "2023-09-15, 1038289", "2023-09-16, 1046587", "2023-09-17, 1055012", "2023-09-18, 1071682",
    "2023-09-19, 1125267", "2023-09-20, 1157089", "2023-09-21, 1179696", "2023-09-22, 1197915",
    "2023-09-23, 1211413", "2023-09-24, 1223934", "2023-09-25, 1237273", "2023-09-26, 1249557",
    "2023-09-27, 1261156", "2023-09-28, 1272657", "2023-09-29, 1294216", "2023-09-30, 1308941",
    "2023-10-01, 1324469", "2023-10-02, 1343949", "2023-10-03, 1361891", "2023-10-04, 1377805",
    "2023-10-05, 1393473", "2023-10-06, 1410649", "2023-10-07, 1425252", "2023-10-08, 1438074",
    "2023-10-09, 1452503", "2023-10-10, 1470776", "2023-10-11, 1489064", "2023-10-12, 1508389",
    "2023-10-13, 1529182", "2023-10-14, 1543696", "2023-10-15, 1557027", "2023-10-16, 1570787",
    "2023-10-17, 1583493", "2023-10-18, 1618452", "2023-10-19, 1646361", "2023-10-20, 1666281",
    "2023-10-21, 1681299", "2023-10-22, 1694865", "2023-10-23, 1709734", "2023-10-24, 1725184",
    "2023-10-25, 1738664", "2023-10-26, 1750386", "2023-10-27, 1761839", "2023-10-28, 1772651",
    "2023-10-29, 1785693", "2023-10-30, 1799713", "2023-10-31, 1811867", "2023-11-01, 1823445",
    "2023-11-02, 1836704", "2023-11-03, 1850723", "2023-11-04, 1863205", "2023-11-05, 1876044",
    "2023-11-06, 1890622", "2023-11-07, 1902887", "2023-11-08, 1918000", "2023-11-09, 1935000",
    "2023-11-10, 1953000", "2023-11-11, 1973500", "2023-11-12, 1994000", "2023-11-13, 2010500",
    "2023-11-14, 2023500", "2023-11-15, 2038000", "2023-11-16, 2052000", "2023-11-17, 2067500",
    "2023-11-18, 2085000", "2023-11-19, 2103500", "2023-11-20, 2124000", "2023-11-21, 2144500",
    "2023-11-22, 2156000", "2023-11-23, 2170500", "2023-11-24, 2189500", "2023-11-25, 2202500",
    "2023-11-26, 2217000", "2023-11-27, 2229000", "2023-11-28, 2252500", "2023-11-29, 2274500",
    "2023-11-30, 2287000", "2023-12-01, 2318000", "2023-12-02, 2339500", "2023-12-03, 2364000",
    "2023-12-04, 2383500", "2023-12-05, 2402000", "2023-12-06, 2418500", "2023-12-07, 2443500",
    "2023-12-08, 2463500", "2023-12-09, 2484000", "2023-12-10, 2493500", "2023-12-11, 2503000",
    "2023-12-12, 2510500", "2023-12-13, 2523500", "2023-12-14, 2538000", "2023-12-15, 2552500",
    "2023-12-16, 2568000", "2023-12-17, 2585000", "2023-12-18, 2611500", "2023-12-19, 2635000",
    "2023-12-20, 2658500", "2023-12-21, 2690000", "2023-12-22, 2712500", "2023-12-23, 2734500",
    "2023-12-24, 2755500", "2023-12-25, 2773500", "2023-12-26, 2791000", "2023-12-27, 2805000",
    "2023-12-28, 2821500", "2023-12-29, 2838000", "2023-12-30, 2854500", "2023-12-31, 2872000",
    "2024-01-01, 2890000", "2024-01-02, 2904500", "2024-01-03, 2917500", "2024-01-04, 2927500",
    "2024-01-05, 2935500", "2024-01-06, 2943000", "2024-01-07, 2961000", "2024-01-08, 2988500",
    "2024-01-09, 3009500", "2024-01-10, 3017000", "2024-01-11, 3024000", "2024-01-12, 3031500",
    "2024-01-13, 3039000", "2024-01-14, 3044000"
]

# Convert the data point strings to datetime objects.
date_rng = [datetime.strptime(row.split(',')[0].strip('"'), "%Y-%m-%d") for row in data_array]
y_values = [int(row.split(',')[1].strip()) for row in data_array]

# Create an initial plot.
fig, ax = plt.subplots(figsize=(10, 6))

# Plot the main data line and specify its z-order for layering.
ax.plot(date_rng, y_values, zorder=2)

# Add a grid and fill the area under the data line.
ax.grid(True, linestyle="-", linewidth=0.4, alpha=0.4)
ax.fill_between(date_rng, y_values, color="skyblue", alpha=0.4, zorder=1)

# Translators - edit these strings to translate into the desired language.
plt.title("Bluesky - Registered Users")
plt.xlabel("Date (YYYY-MM)")
plt.ylabel("Total Registered Users")

# Set the format for the x-axis to display only the first day of each month (ie. YYYY-MM).
ax.xaxis.set_major_locator(mdates.MonthLocator(bymonthday=1))
ax.xaxis.set_major_formatter(mdates.DateFormatter("%Y-%m"))

# Make sure y-axis starts at 0.
ax.set_ylim(bottom=0)

# Format y-axis labels with commas and set tick locations.
y_ticks = ax.get_yticks()
ax.yaxis.set_major_locator(FixedLocator(y_ticks))
ax.set_yticklabels([f'{int(label):,}' for label in y_ticks])

# Hide y-axis offset number (1e6, etc.)
ax.yaxis.offsetText.set_visible(False)

'''
Logic to highlight and label the first day of each month:
     1. Create an empty set to keep track of processed months.
     2. Loop through each date-value pair.
     3. Check if the day is the 1st of the month or if the month hasn't been processed yet.
     4. Place a scatter dot on the first day of the unprocessed month.
     5. Annotate the scatter dot with the corresponding value.
     6. Add the month to the set to avoid processing it again.
'''
months = set()
for date, value in zip(date_rng, y_values):
     if date.day == 1 or date.strftime("%Y-%m") not in months:
          ax.scatter(date, value, color='C0', marker='o', alpha=1, zorder=3)
          ax.annotate(f'{value:,}', (date, value), textcoords="offset points", xytext=(0, 10), ha='center')
          months.add(date.strftime("%Y-%m"))

# Optimize for visibility, then display.
plt.tight_layout()
plt.show()

Licenza

Pubblico dominio Quest'opera è basata su un'opera nel pubblico dominio, ed è stata ritoccata digitalmente o modificata. Quest'opera derivata è stata (o lo è ora) rilasciata nel pubblico dominio dal suo autore, VintageNebula. La norma si applica in tutto il mondo.

In alcuni Paesi questo potrebbe non essere legalmente possibile. In tal caso:
VintageNebula garantisce a chiunque il diritto di usare quest'opera per qualsiasi scopo, senza alcuna condizione, a meno che tali condizioni non siano richieste dalla legge.

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Line chart depicting the growth of Bluesky, a social platform, from May 2023 to January 2024.

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Data/OraMiniaturaDimensioniUtenteCommento
attuale04:40, 15 gen 2024Miniatura della versione delle 04:40, 15 gen 2024960 × 576 (38 KB)VintageNebulaUpdate data to January 2024
03:50, 6 nov 2023Miniatura della versione delle 03:50, 6 nov 2023960 × 576 (37 KB)VintageNebulaUpdate data to November 2023
03:44, 9 ott 2023Miniatura della versione delle 03:44, 9 ott 2023900 × 540 (48 KB)VintageNebulaUploaded a work by Data compiled by m3ta.uk (Pedro) and vqv.app (Eddie). Chart created by VintageNebula (myself). from Data was obtained from requests to the public-facing Bluesky API, which were archived and rendered for display at https://vqv.app/stats/chart. Chart generated using the archived Bluesky API data created by VintageNebula (myself) using Matplotlib. with UploadWizard

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Estratto da "https://it.wikipedia.org/wiki/File:Bluesky_Registered_Users.svg"