pandas: powerful Python data analysis toolkit - 0.14.0GH4163, GH5950, GH6292). All databases supported by SQLAlchemy can be used, such as PostgreSQL, MySQL, Oracle, Microsoft SQL server (see documentation of SQLAlchemy on included dialects). The functionality functionality of providing DBAPI connection objects will only be supported for sqlite3 in the future. The ’mysql’ flavor is deprecated. The new functions read_sql_query() and read_sql_table() are introduced. The read_frame, frame_query, write_frame. Warning: The support for the ‘mysql’ flavor when using DBAPI connection objects has been deprecated. MySQL will be further supported with SQLAlchemy engines (GH6900). 10 码力 | 1349 页 | 7.67 MB | 1 年前3
pandas: powerful Python data analysis toolkit - 0.15Index.all, and Index.any no longer support the out and keepdims parameters, which existed for compatibility with ndarray. Various index types no longer support the all and any aggregation functions and recommend that all users upgrade to this version. Warning: pandas >= 0.15.0 will no longer support compatibility with NumPy versions < 1.7.0. If you want to use the latest versions of pandas, please upgrade Timedelta, which is a subclass of datetime.timedelta, and behaves in a similar manner, but allows compatibility with np.timedelta64 types as well as a host of custom representation, parsing, and attributes0 码力 | 1579 页 | 9.15 MB | 1 年前3
pandas: powerful Python data analysis toolkit - 0.15.1recommend that all users upgrade to this version. Warning: pandas >= 0.15.0 will no longer support compatibility with NumPy versions < 1.7.0. If you want to use the latest versions of pandas, please upgrade Timedelta, which is a subclass of datetime.timedelta, and behaves in a similar manner, but allows compatibility with np.timedelta64 types as well as a host of custom representation, parsing, and attributes importing Stata files (GH8527) • DataFrame.to_stata and StataWriter check string length for compatibility with limitations imposed in dta files where fixed-width strings must contain 244 or fewer characters0 码力 | 1557 页 | 9.10 MB | 1 年前3
pandas: powerful Python data analysis toolkit - 0.17.0recommend that all users upgrade to this version. Warning: pandas >= 0.17.0 will no longer support compatibility with Python version 3.2 (GH9118) Warning: The pandas.io.data package is deprecated and will be plain text can optionally align with Unicode East Asian Width, see here • Compatibility with Python 3.5 (GH11097) • Compatibility with matplotlib 1.5.0 (GH11111) Check the API Changes and deprecations read Stata 118 type files. (GH9882) • msgpack submodule has been updated to 0.4.6 with backward compatibility (GH10581) • DataFrame.to_dict now accepts orient=’index’ keyword argument (GH10844). • DataFrame0 码力 | 1787 页 | 10.76 MB | 1 年前3
pandas: powerful Python data analysis toolkit - 0.20.3nth() changes . . . . . . . . . . . . . . . . . . . . . . . . . . 101 1.7.3.2 numpy function compatibility . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 103 1.7.3.3 Using .apply on groupby . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 386 3.5.1.3 Backwards Compatibility . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 386 3.5.2 Testing With Continuous . . . . . . . 1083 24.8.10 External Compatibility . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1084 24.8.11 Backwards Compatibility . . . . . . . . . . . . . . . . . . .0 码力 | 2045 页 | 9.18 MB | 1 年前3
pandas: powerful Python data analysis toolkit - 0.19.0nth() changes . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 52 numpy function compatibility . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 53 Using .apply on groupby . . . . . . . . 976 25.8.10 External Compatibility . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 978 25.8.11 Backwards Compatibility . . . . . . . . . . . . . . . . . . . sql functions when sqlalchemy is not installed and a connection string is used (GH11920). • Compatibility with matplotlib 2.0. Older versions of pandas should also work with matplotlib 2.0 (GH13333)0 码力 | 1937 页 | 12.03 MB | 1 年前3
pandas: powerful Python data analysis toolkit - 0.19.1nth() changes . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 53 numpy function compatibility . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 55 Using .apply on groupby . . . . . . . . 979 25.8.10 External Compatibility . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 980 25.8.11 Backwards Compatibility . . . . . . . . . . . . . . . . . . . sql functions when sqlalchemy is not installed and a connection string is used (GH11920). • Compatibility with matplotlib 2.0. Older versions of pandas should also work with matplotlib 2.0 (GH13333)0 码力 | 1943 页 | 12.06 MB | 1 年前3
pandas: powerful Python data analysis toolkit - 0.20.2nth() changes . . . . . . . . . . . . . . . . . . . . . . . . . . 99 1.6.3.2 numpy function compatibility . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 101 1.6.3.3 Using .apply on groupby . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 384 3.5.1.3 Backwards Compatibility . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 384 3.5.2 Testing With Continuous . . . . . . . 1078 24.8.10 External Compatibility . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1080 24.8.11 Backwards Compatibility . . . . . . . . . . . . . . . . . . .0 码力 | 1907 页 | 7.83 MB | 1 年前3
pandas: powerful Python data analysis toolkit - 1.0.0MultiIndex.names to access the names, and Index.set_names() to update the names. For backwards compatibility, you can still access the names via the levels. In [24]: mi = pd.MultiIndex.from_product([[1 sqlalchemy pyarrow 0.12.0 Parquet, ORC (requires 0.13.0), and feather reading / writing pymysql 0.7.11 MySQL engine for sqlalchemy pyreadstat SPSS files (.sav) reading pytables 3.4.2 HDF5 reading / writing transfer of DataFrame objects from pandas to R, one option is to use HDF5 files, see External compatibility for an example. Quick reference We’ll start off with a quick reference guide pairing some common0 码力 | 3015 页 | 10.78 MB | 1 年前3
pandas: powerful Python data analysis toolkit - 0.21.1nth() changes . . . . . . . . . . . . . . . . . . . . . . . . . . 130 1.9.3.2 numpy function compatibility . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 132 1.9.3.3 Using .apply on groupby . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 413 3.5.1.3 Backwards Compatibility . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 414 3.5.2 Testing With Continuous . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1117 24.8.10 External Compatibility . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1119 24.8.11 Performance0 码力 | 2207 页 | 8.59 MB | 1 年前3
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