==> Options --HEAD Install HEAD version ==> Caveats zlib is keg-only, which means it was not symlinked into /opt/homebrew, because macOS already provides this software and installing another version in parallel can cause all kinds of trouble. For compilers to find zlib you may need to set: export LDFLAGS="-L/opt/homebrew/opt/zlib/lib" export CPPFLAGS="-I/opt/homebrew/opt/zlib/include" ==> Analytics install: 1,802 (30 days), 47,333 (90 days), 1,139,842 (365 days) install-on-request: 504 (30 days), 17,580 (90 days), 480,877 (365 days) build-error: 0 (30 days)

这是一个 Homebrew 的安装日志，它告诉你安装了一个名为 zlib 的软件，但由于 macOS 已经提供了这个软件，所以它没有被链接到 /opt/homebrew 目录下，避免了可能会出现的问题。如果你需要编译器找到 zlib，你需要设置一些环境变量，具体是设置 `LDFLAGS` 和 `CPPFLAGS`。安装分析数据告诉你在过去的 30 天、90 天和 365 天内，这个软件的安装情况、请求安装情况和构建错误情况。

相关问题

If you installed this formula with the registration option (default), you'll need to manually remove [ODBC Driver 13 for SQL Server] section from odbcinst.ini after the formula is uninstalled. This can be done by executing the following command: odbcinst -u -d -n "ODBC Driver 13 for SQL Server" ==> Summary 🍺 /opt/homebrew/Cellar/msodbcsql/13.1.9.2: 10 files, 2.6MB, built in 15 seconds ==> Caveats ==> msodbcsql If you installed this formula with the registration option (default), you'll need to manually remove [ODBC Driver 13 for SQL Server] section from odbcinst.ini after the formula is uninstalled. This can be done by executing the following command: odbcinst -u -d -n "ODBC Driver 13 for SQL Server"

这个提示意味着，如果你使用默认的注册选项安装了 Microsoft ODBC Driver for SQL Server，那么在卸载该公式后，你需要手动从 `odbcinst.ini` 中删除 `[ODBC Driver 13 for SQL Server]` 部分。这可以通过执行以下命令来完成：

odbcinst -u -d -n "ODBC Driver 13 for SQL Server"

执行此命令将会从 `odbcinst.ini` 中删除 `[ODBC Driver 13 for SQL Server]` 部分。

请注意，`odbcinst.ini` 文件通常位于 `/etc` 目录下。如果你使用的是 macOS 平台，则可能需要使用超级用户权限才能编辑该文件。

希望这可以帮助你解决问题。

def feature_Kmeans(data,label): mms = MinMaxScaler() feats = [f for f in data.columns if f not in ['loan_id', 'user_id', 'isDefault']] data = data[feats] mmsModel = mms.fit_transform(data.loc[data['class'] == label]) clf = KMeans(5, random_state=2021) pre = clf.fit(mmsModel) test = pre.labels_ final_data = pd.Series(test, index=data.loc[data['class'] == label].index) if label == 1: /opt/conda/envs/python35-paddle120-env/lib/python3.7/site-packages/ipykernel_launcher.py:74: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy /opt/conda/envs/python35-paddle120-env/lib/python3.7/site-packages/ipykernel_launcher.py:75: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy /opt/conda/envs/python35-paddle120-env/lib/python3.7/site-packages/ipykernel_launcher.py:76: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy

这段代码中出现了 `SettingWithCopyWarning` 警告，警告的原因是在对 DataFrame 进行切片操作之后，对切片对象进行了赋值操作，这可能会导致原 DataFrame 的值也被改变，进而导致错误的结果。建议使用 `.loc` 或 `.iloc` 进行切片并进行赋值操作，以避免这个警告的出现。你可以使用如下代码来避免这个警告：

if label == 1:
    final_data = pd.DataFrame({'class': final_data})
    data.loc[data['class'] == label, 'class'] = final_data['class']