Index(data, **_)
Index
Index.is_monotonic
Return boolean scalar if values in the object are monotonic_increasing.
Index.is_monotonic_decreasing
Return boolean scalar if values in the object are monotonic_decreasing.
Index.is_monotonic_increasing
Index.name
Index.names
Index.ndim
Index.size
Index.memory_usage([deep])
Index.memory_usage
Memory usage of the values.
Index.all()
Index.all
Index.any()
Index.any
Index.drop(labels[, errors])
Index.drop
Make new Index with passed list of labels deleted.
Index.drop_duplicates([keep, method])
Index.drop_duplicates
Return Index with duplicate values removed.
Index.duplicated([keep])
Index.duplicated
Indicate duplicate index values.
Index.max([axis, skipna])
Index.max
Index.min([axis, skipna])
Index.min
Index.rename(name[, inplace])
Index.rename
Alter Index or MultiIndex name.
Index.set_names(names[, level, inplace])
Index.set_names
Set Index or MultiIndex name.
Index.fillna([value, downcast])
Index.fillna
Fill NA/NaN values with the specified value.
Index.dropna([how])
Index.dropna
Return Index without NA/NaN values.
Index.isna()
Index.isna
Detect missing values.
Index.notna()
Index.notna
Detect existing (non-missing) values.
Index.astype(dtype[, copy])
Index.astype
Create an Index with values cast to dtypes.
Index.map(mapper[, na_action, dtype, …])
Index.map
Map values using input correspondence (a dict, Series, or function).
Index.to_frame([index, name])
Index.to_frame
Create a DataFrame with a column containing the Index.
Index.to_series([index, name])
Index.to_series
Create a Series with both index and values equal to the index keys.