19. Write a python program to check the detail of pandas module.
The output is:
Expected Answer:
----------------------------pandas detail----------------------------
['Categorical', 'CategoricalDtype', 'CategoricalIndex', 'DataFrame', 'DateOffset', 'DatetimeIndex',
'DatetimeTZDtype', 'ExcelFile', 'ExcelWriter', 'Float64Index', 'Grouper', 'HDFStore',
'Index', 'IndexSlice', 'Int16Dtype', 'Int32Dtype', 'Int64Dtype', 'Int64Index', 'Int8Dtype',
'Interval', 'IntervalDtype', 'IntervalIndex', 'MultiIndex', 'NaT', 'Panel', 'Period',
'PeriodDtype', 'PeriodIndex', 'RangeIndex', 'Series', 'SparseArray', 'SparseDataFrame',
'SparseDtype', 'SparseSeries', 'TimeGrouper', 'Timedelta', 'TimedeltaIndex', 'Timestamp',
'UInt16Dtype', 'UInt32Dtype', 'UInt64Dtype', 'UInt64Index', 'UInt8Dtype',
'__builtins__', '__cached__', '__doc__', '__docformat__', '__file__', '__git_version__',
'__loader__', '__name__', '__package__', '__path__', '__spec__', '__version__',
'_hashtable', '_lib', '_libs', '_np_version_under1p13', '_np_version_under1p14',
'_np_version_under1p15', '_np_version_under1p16', '_np_version_under1p17', '_tslib',
'_version', 'api', 'array', 'arrays', 'bdate_range', 'compat', 'concat', 'core',
'crosstab', 'cut', 'date_range', 'datetime', 'describe_option', 'errors', 'eval',
'factorize', 'get_dummies', 'get_option', 'infer_freq', 'interval_range', 'io', 'isna',
'isnull', 'lreshape', 'melt', 'merge', 'merge_asof', 'merge_ordered', 'notna',
'notnull', 'np', 'offsets', 'option_context', 'options', 'pandas', 'period_range',
'pivot', 'pivot_table', 'plotting', 'qcut', 'read_clipboard', 'read_csv', 'read_excel',
'read_feather', 'read_fwf', 'read_gbq', 'read_hdf', 'read_html', 'read_json',
'read_msgpack', 'read_parquet', 'read_pickle', 'read_sas', 'read_sql', 'read_sql_query',
'read_sql_table', 'read_stata', 'read_table', 'reset_option', 'set_eng_float_format',
'set_option', 'show_versions', 'test', 'testing', 'timedelta_range', 'to_datetime',
'to_msgpack', 'to_numeric', 'to_pickle', 'to_timedelta', 'tseries', 'unique', 'util',
'value_counts', 'wide_to_long']
Answer:
import pandas pandas_detail = dir(pandas) print('----------------------------pandas detail----------------------------') print(pandas_detail)
More Exercises:
Python String ExercisesMore Numpy Exercises:
Numpy String ExercisesMore Pandas Exercises:
Pandas Series ExercisesMore Tutorials:
Python Installation - Linux (Ubuntu)