GITHUB . COM {}

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• Cryptocurrency
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Github.com utilizes WORDPRESS.

Traffic Estimate {📈}

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🚀🌠 Tremendous Traffic: 10M - 20M visitors per month


Based on our best estimate, this website will receive around 10,653,634 visitors per month in the current month.

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Subscription Packages {💳}

How Much Does Github.com Make? {💰}

Subscription Packages {💳}

Prices on github.com are in US Dollars ($). They range from $4.00/month to $21.00/month.
We estimate that the site has approximately 5,316,035 paying customers.
The estimated monthly recurring revenue (MRR) is $22,327,346.
The estimated annual recurring revenues (ARR) are $267,928,149.

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It is strange but we were not able to detect any theme on the page.

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Keywords {🔍}

nan, rhshadrach, bug, asindexfalse, groupbydescribe, incorrect, sign, foo, std, min, projects, issue, count, max, groupers, zhongxj, navigation, pull, requests, actions, security, closed, dataframe, npnan, printgbdescribe, column, output, groupby, commented, asindextrue, github, type, milestone, footer, skip, content, menu, product, solutions, resources, open, source, enterprise, pricing, search, jump, pandasdev, pandas, public, notifications,

Topics {✒️}

personal information bug as_index=false produces as_index=false describes type projects df = dataframe rhshadrach changed as_index=false projects milestone as_index=true nan gb = df bug incorrect milestone relationships wrong output github ['foo2'] print groupby groupers print gb output foo2 sign skip jump describe foo np bar baz columns=[ column count seriesgroupby foo1 assigned result works intended agree free join conversation account development branches share

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Schema {🗺️}

DiscussionForumPosting:
      context:https://schema.org
      headline:BUG: groupby.describe with as_index=False incorrect
      articleBody:``` df = DataFrame( [[1, 2, "foo"], [1, np.nan, "bar"], [3, np.nan, "baz"]], columns=["A", "B", "C"], ) gb = df.groupby("A", as_index=False) print(gb.describe()) # A ... B # count mean std min 25% 50% 75% ... mean std min 25% 50% 75% max # 0 2.0 1.0 0.0 1.0 1.0 1.0 1.0 ... 2.0 NaN 2.0 2.0 2.0 2.0 2.0 # 1 1.0 3.0 NaN 3.0 3.0 3.0 3.0 ... NaN NaN NaN NaN NaN NaN NaN ``` Instead, column A should just have the groupers ``` A B count mean std min 25% 50% 75% max 0 1 1.0 2.0 NaN 2.0 2.0 2.0 2.0 2.0 1 3 0.0 NaN NaN NaN NaN NaN NaN NaN ``` We get different, but also incorrect, output for SeriesGroupBy: ``` df = DataFrame( { "foo1": ["one", "two", "two", "three", "one", "two"], "foo2": [1, 2, 4, 4, 5, 6], } ) gb = df.groupby("foo1", as_index=False)['foo2'] print(gb.describe()) # foo1 0 one # 1 three # 2 two # count 0 2.0 # 1 1.0 # 2 3.0 # mean 0 3.0 # 1 4.0 # 2 4.0 # std 0 2.828427 # 1 NaN # 2 2.0 # min 0 1.0 # 1 4.0 # 2 2.0 # 25% 0 2.0 # 1 4.0 # 2 3.0 # 50% 0 3.0 # 1 4.0 # 2 4.0 # 75% 0 4.0 # 1 4.0 # 2 5.0 # max 0 5.0 # 1 4.0 # 2 6.0 # dtype: object ```
      author:
         url:https://github.com/rhshadrach
         type:Person
         name:rhshadrach
      datePublished:2022-10-22T23:21:01.000Z
      interactionStatistic:
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      url:https://github.com/49256/pandas/issues/49256
      context:https://schema.org
      headline:BUG: groupby.describe with as_index=False incorrect
      articleBody:``` df = DataFrame( [[1, 2, "foo"], [1, np.nan, "bar"], [3, np.nan, "baz"]], columns=["A", "B", "C"], ) gb = df.groupby("A", as_index=False) print(gb.describe()) # A ... B # count mean std min 25% 50% 75% ... mean std min 25% 50% 75% max # 0 2.0 1.0 0.0 1.0 1.0 1.0 1.0 ... 2.0 NaN 2.0 2.0 2.0 2.0 2.0 # 1 1.0 3.0 NaN 3.0 3.0 3.0 3.0 ... NaN NaN NaN NaN NaN NaN NaN ``` Instead, column A should just have the groupers ``` A B count mean std min 25% 50% 75% max 0 1 1.0 2.0 NaN 2.0 2.0 2.0 2.0 2.0 1 3 0.0 NaN NaN NaN NaN NaN NaN NaN ``` We get different, but also incorrect, output for SeriesGroupBy: ``` df = DataFrame( { "foo1": ["one", "two", "two", "three", "one", "two"], "foo2": [1, 2, 4, 4, 5, 6], } ) gb = df.groupby("foo1", as_index=False)['foo2'] print(gb.describe()) # foo1 0 one # 1 three # 2 two # count 0 2.0 # 1 1.0 # 2 3.0 # mean 0 3.0 # 1 4.0 # 2 4.0 # std 0 2.828427 # 1 NaN # 2 2.0 # min 0 1.0 # 1 4.0 # 2 2.0 # 25% 0 2.0 # 1 4.0 # 2 3.0 # 50% 0 3.0 # 1 4.0 # 2 4.0 # 75% 0 4.0 # 1 4.0 # 2 5.0 # max 0 5.0 # 1 4.0 # 2 6.0 # dtype: object ```
      author:
         url:https://github.com/rhshadrach
         type:Person
         name:rhshadrach
      datePublished:2022-10-22T23:21:01.000Z
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      url:https://github.com/49256/pandas/issues/49256
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      name:rhshadrach
      url:https://github.com/rhshadrach
      name:rhshadrach
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      interactionType:https://schema.org/CommentAction
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External Links {🔗}(2)

• How much does https://github.blog earn?
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