docstring . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2983 4.3.3 How to build the pandas documentation . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2983 4.3.4 Previewing the by parameter to DataFrame.sort_values() may refer to either columns or index level names. # Build MultiIndex In [323]: idx = pd.MultiIndex.from_tuples( .....: [("a", 1), ("a", 2), ("a", 2), ("b" ("b", 2), ("b", 1), ("b", 1)] .....: ) .....: In [324]: idx.names = ["first", "second"] # Build DataFrame In [325]: df_multi = pd.DataFrame({"A": np.arange(6, 0, -1)}, index=idx) In [326]: df_multi Out[326]:

docstring . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2640 4.3.3 How to build the pandas documentation . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2640 4.3.4 Previewing the by parameter to DataFrame.sort_values() may refer to either columns or index level names. # Build MultiIndex In [323]: idx = pd.MultiIndex.from_tuples( .....: [("a", 1), ("a", 2), ("a", 2), ("b" ("b", 2), ("b", 1), ("b", 1)] .....: ) .....: In [324]: idx.names = ["first", "second"] # Build DataFrame In [325]: df_multi = pd.DataFrame({"A": np.arange(6, 0, -1)}, index=idx) In [326]: df_multi Out[326]:

docstring . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2719 4.3.3 How to build the pandas documentation . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2719 4.3.4 Previewing the by parameter to DataFrame.sort_values() may refer to either columns or index level names. # Build MultiIndex In [323]: idx = pd.MultiIndex.from_tuples( .....: [("a", 1), ("a", 2), ("a", 2), ("b" ("b", 2), ("b", 1), ("b", 1)] .....: ) .....: In [324]: idx.names = ["first", "second"] # Build DataFrame In [325]: df_multi = pd.DataFrame({"A": np.arange(6, 0, -1)}, index=idx) In [326]: df_multi Out[326]:

docstring . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2719 4.3.3 How to build the pandas documentation . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2719 4.3.4 Previewing the by parameter to DataFrame.sort_values() may refer to either columns or index level names. # Build MultiIndex In [323]: idx = pd.MultiIndex.from_tuples( .....: [("a", 1), ("a", 2), ("a", 2), ("b" ("b", 2), ("b", 1), ("b", 1)] .....: ) .....: In [324]: idx.names = ["first", "second"] # Build DataFrame In [325]: df_multi = pd.DataFrame({"A": np.arange(6, 0, -1)}, index=idx) In [326]: df_multi Out[326]:

docstring . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2811 4.3.3 How to build the pandas documentation . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2811 4.3.4 Previewing the by parameter to DataFrame.sort_values() may refer to either columns or index level names. # Build MultiIndex In [323]: idx = pd.MultiIndex.from_tuples( .....: [("a", 1), ("a", 2), ("a", 2), ("b" ("b", 2), ("b", 1), ("b", 1)] .....: ) .....: In [324]: idx.names = ["first", "second"] # Build DataFrame In [325]: df_multi = pd.DataFrame({"A": np.arange(6, 0, -1)}, index=idx) In [326]: df_multi Out[326]:

docstring . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2813 4.3.3 How to build the pandas documentation . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2813 4.3.4 Previewing the by parameter to DataFrame.sort_values() may refer to either columns or index level names. # Build MultiIndex In [323]: idx = pd.MultiIndex.from_tuples( .....: [("a", 1), ("a", 2), ("a", 2), ("b" ("b", 2), ("b", 1), ("b", 1)] .....: ) .....: In [324]: idx.names = ["first", "second"] # Build DataFrame In [325]: df_multi = pd.DataFrame({"A": np.arange(6, 0, -1)}, index=idx) In [326]: df_multi Out[326]:

1.1.0 xlsxwriter 0.9.8 xlwt 1.2.0 See Dependencies and Optional dependencies for more. 1.5.13 Build Changes Pandas has added a pyproject.toml file and will no longer include cythonized files in the you. If you’re building pandas from source, you should no longer need to install Cython into your build environment before calling pip install pandas. 1.5.14 Other API changes • core.groupby.GroupBy.transform names. # Build MultiIndex In [309]: idx = pd.MultiIndex.from_tuples([('a', 1), ('a', 2), ('a', 2), .....: ('b', 2), ('b', 1), ('b', 1)]) .....: In [310]: idx.names = ['first', 'second'] # Build DataFrame

the by parameter to DataFrame.sort_values() may refer to either columns or index level names. # Build MultiIndex In [323]: idx = pd.MultiIndex.from_tuples( .....: [("a", 1), ("a", 2), ("a", 2), ("b" ("b", 2), ("b", 1), ("b", 1)] .....: ) .....: In [324]: idx.names = ["first", "second"] # Build DataFrame In [325]: df_multi = pd.DataFrame({"A": np.arange(6, 0, -1)}, index=idx) In [326]: df_multi Out[326]: includes information on the field names, types, and other attributes. You can use the orient table to build a JSON string with two fields, schema and data. In [268]: df = pd.DataFrame( .....: { .....: "A":

the by parameter to DataFrame.sort_values() may refer to either columns or index level names. # Build MultiIndex In [323]: idx = pd.MultiIndex.from_tuples( .....: [("a", 1), ("a", 2), ("a", 2), ("b" ("b", 2), ("b", 1), ("b", 1)] .....: ) .....: In [324]: idx.names = ["first", "second"] # Build DataFrame In [325]: df_multi = pd.DataFrame({"A": np.arange(6, 0, -1)}, index=idx) In [326]: df_multi Out[326]: includes information on the field names, types, and other attributes. You can use the orient table to build a JSON string with two fields, schema and data. In [268]: df = pd.DataFrame( .....: { .....: "A":

names. # Build MultiIndex In [322]: idx = pd.MultiIndex.from_tuples([('a', 1), ('a', 2), ('a', 2), .....: ('b', 2), ('b', 1), ('b', 1)]) .....: In [323]: idx.names = ['first', 'second'] # Build DataFrame includes information on the field names, types, and other attributes. You can use the orient table to build a JSON string with two fields, schema and data. In [269]: df = pd.DataFrame({'A': [1, 2, 3], .. an offset of 0. In [272]: from pandas.io.json import build_table_schema In [273]: s = pd.Series(pd.date_range('2016', periods=4)) In [274]: build_table_schema(s) Out[274]: {'fields': [{'name': 'index'