doc_content stringlengths 1 386k | doc_id stringlengths 5 188 |
|---|---|
pandas.DataFrame.update DataFrame.update(other, join='left', overwrite=True, filter_func=None, errors='ignore')[source]
Modify in place using non-NA values from another DataFrame. Aligns on indices. There is no return value. Parameters
other:DataFrame, or object coercible into a DataFrame
Should have at least... | pandas.reference.api.pandas.dataframe.update |
pandas.DataFrame.value_counts DataFrame.value_counts(subset=None, normalize=False, sort=True, ascending=False, dropna=True)[source]
Return a Series containing counts of unique rows in the DataFrame. New in version 1.1.0. Parameters
subset:list-like, optional
Columns to use when counting unique combinations.... | pandas.reference.api.pandas.dataframe.value_counts |
pandas.DataFrame.values propertyDataFrame.values
Return a Numpy representation of the DataFrame. Warning We recommend using DataFrame.to_numpy() instead. Only the values in the DataFrame will be returned, the axes labels will be removed. Returns
numpy.ndarray
The values of the DataFrame. See also DataFr... | pandas.reference.api.pandas.dataframe.values |
pandas.DataFrame.var DataFrame.var(axis=None, skipna=True, level=None, ddof=1, numeric_only=None, **kwargs)[source]
Return unbiased variance over requested axis. Normalized by N-1 by default. This can be changed using the ddof argument. Parameters
axis:{index (0), columns (1)}
skipna:bool, default True
Excl... | pandas.reference.api.pandas.dataframe.var |
pandas.DataFrame.where DataFrame.where(cond, other=NoDefault.no_default, inplace=False, axis=None, level=None, errors='raise', try_cast=NoDefault.no_default)[source]
Replace values where the condition is False. Parameters
cond:bool Series/DataFrame, array-like, or callable
Where cond is True, keep the origina... | pandas.reference.api.pandas.dataframe.where |
pandas.DataFrame.xs DataFrame.xs(key, axis=0, level=None, drop_level=True)[source]
Return cross-section from the Series/DataFrame. This method takes a key argument to select data at a particular level of a MultiIndex. Parameters
key:label or tuple of label
Label contained in the index, or partially in a Multi... | pandas.reference.api.pandas.dataframe.xs |
pandas.date_range pandas.date_range(start=None, end=None, periods=None, freq=None, tz=None, normalize=False, name=None, closed=NoDefault.no_default, inclusive=None, **kwargs)[source]
Return a fixed frequency DatetimeIndex. Returns the range of equally spaced time points (where the difference between any two adjacen... | pandas.reference.api.pandas.date_range |
pandas.DatetimeIndex classpandas.DatetimeIndex(data=None, freq=NoDefault.no_default, tz=None, normalize=False, closed=None, ambiguous='raise', dayfirst=False, yearfirst=False, dtype=None, copy=False, name=None)[source]
Immutable ndarray-like of datetime64 data. Represented internally as int64, and which can be boxe... | pandas.reference.api.pandas.datetimeindex |
pandas.DatetimeIndex.ceil DatetimeIndex.ceil(*args, **kwargs)[source]
Perform ceil operation on the data to the specified freq. Parameters
freq:str or Offset
The frequency level to ceil the index to. Must be a fixed frequency like ‘S’ (second) not ‘ME’ (month end). See frequency aliases for a list of possible... | pandas.reference.api.pandas.datetimeindex.ceil |
pandas.DatetimeIndex.date propertyDatetimeIndex.date
Returns numpy array of python datetime.date objects. Namely, the date part of Timestamps without time and timezone information. | pandas.reference.api.pandas.datetimeindex.date |
pandas.DatetimeIndex.day propertyDatetimeIndex.day
The day of the datetime. Examples
>>> datetime_series = pd.Series(
... pd.date_range("2000-01-01", periods=3, freq="D")
... )
>>> datetime_series
0 2000-01-01
1 2000-01-02
2 2000-01-03
dtype: datetime64[ns]
>>> datetime_series.dt.day
0 1
1 2
2 3... | pandas.reference.api.pandas.datetimeindex.day |
pandas.DatetimeIndex.day_name DatetimeIndex.day_name(*args, **kwargs)[source]
Return the day names of the DateTimeIndex with specified locale. Parameters
locale:str, optional
Locale determining the language in which to return the day name. Default is English locale. Returns
Index
Index of day names. ... | pandas.reference.api.pandas.datetimeindex.day_name |
pandas.DatetimeIndex.day_of_week propertyDatetimeIndex.day_of_week
The day of the week with Monday=0, Sunday=6. Return the day of the week. It is assumed the week starts on Monday, which is denoted by 0 and ends on Sunday which is denoted by 6. This method is available on both Series with datetime values (using the... | pandas.reference.api.pandas.datetimeindex.day_of_week |
pandas.DatetimeIndex.day_of_year propertyDatetimeIndex.day_of_year
The ordinal day of the year. | pandas.reference.api.pandas.datetimeindex.day_of_year |
pandas.DatetimeIndex.dayofweek propertyDatetimeIndex.dayofweek
The day of the week with Monday=0, Sunday=6. Return the day of the week. It is assumed the week starts on Monday, which is denoted by 0 and ends on Sunday which is denoted by 6. This method is available on both Series with datetime values (using the dt ... | pandas.reference.api.pandas.datetimeindex.dayofweek |
pandas.DatetimeIndex.dayofyear propertyDatetimeIndex.dayofyear
The ordinal day of the year. | pandas.reference.api.pandas.datetimeindex.dayofyear |
pandas.DatetimeIndex.floor DatetimeIndex.floor(*args, **kwargs)[source]
Perform floor operation on the data to the specified freq. Parameters
freq:str or Offset
The frequency level to floor the index to. Must be a fixed frequency like ‘S’ (second) not ‘ME’ (month end). See frequency aliases for a list of poss... | pandas.reference.api.pandas.datetimeindex.floor |
pandas.DatetimeIndex.freq propertyDatetimeIndex.freq
Return the frequency object if it is set, otherwise None. | pandas.reference.api.pandas.datetimeindex.freq |
pandas.DatetimeIndex.freqstr propertyDatetimeIndex.freqstr
Return the frequency object as a string if its set, otherwise None. | pandas.reference.api.pandas.datetimeindex.freqstr |
pandas.DatetimeIndex.hour propertyDatetimeIndex.hour
The hours of the datetime. Examples
>>> datetime_series = pd.Series(
... pd.date_range("2000-01-01", periods=3, freq="h")
... )
>>> datetime_series
0 2000-01-01 00:00:00
1 2000-01-01 01:00:00
2 2000-01-01 02:00:00
dtype: datetime64[ns]
>>> datetime_ser... | pandas.reference.api.pandas.datetimeindex.hour |
pandas.DatetimeIndex.indexer_at_time DatetimeIndex.indexer_at_time(time, asof=False)[source]
Return index locations of values at particular time of day (e.g. 9:30AM). Parameters
time:datetime.time or str
Time passed in either as object (datetime.time) or as string in appropriate format (“%H:%M”, “%H%M”, “%I:%... | pandas.reference.api.pandas.datetimeindex.indexer_at_time |
pandas.DatetimeIndex.indexer_between_time DatetimeIndex.indexer_between_time(start_time, end_time, include_start=True, include_end=True)[source]
Return index locations of values between particular times of day (e.g., 9:00-9:30AM). Parameters
start_time, end_time:datetime.time, str
Time passed either as object... | pandas.reference.api.pandas.datetimeindex.indexer_between_time |
pandas.DatetimeIndex.inferred_freq DatetimeIndex.inferred_freq
Tries to return a string representing a frequency guess, generated by infer_freq. Returns None if it can’t autodetect the frequency. | pandas.reference.api.pandas.datetimeindex.inferred_freq |
pandas.DatetimeIndex.is_leap_year propertyDatetimeIndex.is_leap_year
Boolean indicator if the date belongs to a leap year. A leap year is a year, which has 366 days (instead of 365) including 29th of February as an intercalary day. Leap years are years which are multiples of four with the exception of years divisib... | pandas.reference.api.pandas.datetimeindex.is_leap_year |
pandas.DatetimeIndex.is_month_end propertyDatetimeIndex.is_month_end
Indicates whether the date is the last day of the month. Returns
Series or array
For Series, returns a Series with boolean values. For DatetimeIndex, returns a boolean array. See also is_month_start
Return a boolean indicating whether t... | pandas.reference.api.pandas.datetimeindex.is_month_end |
pandas.DatetimeIndex.is_month_start propertyDatetimeIndex.is_month_start
Indicates whether the date is the first day of the month. Returns
Series or array
For Series, returns a Series with boolean values. For DatetimeIndex, returns a boolean array. See also is_month_start
Return a boolean indicating whet... | pandas.reference.api.pandas.datetimeindex.is_month_start |
pandas.DatetimeIndex.is_quarter_end propertyDatetimeIndex.is_quarter_end
Indicator for whether the date is the last day of a quarter. Returns
is_quarter_end:Series or DatetimeIndex
The same type as the original data with boolean values. Series will have the same name and index. DatetimeIndex will have the sam... | pandas.reference.api.pandas.datetimeindex.is_quarter_end |
pandas.DatetimeIndex.is_quarter_start propertyDatetimeIndex.is_quarter_start
Indicator for whether the date is the first day of a quarter. Returns
is_quarter_start:Series or DatetimeIndex
The same type as the original data with boolean values. Series will have the same name and index. DatetimeIndex will have ... | pandas.reference.api.pandas.datetimeindex.is_quarter_start |
pandas.DatetimeIndex.is_year_end propertyDatetimeIndex.is_year_end
Indicate whether the date is the last day of the year. Returns
Series or DatetimeIndex
The same type as the original data with boolean values. Series will have the same name and index. DatetimeIndex will have the same name. See also is_yea... | pandas.reference.api.pandas.datetimeindex.is_year_end |
pandas.DatetimeIndex.is_year_start propertyDatetimeIndex.is_year_start
Indicate whether the date is the first day of a year. Returns
Series or DatetimeIndex
The same type as the original data with boolean values. Series will have the same name and index. DatetimeIndex will have the same name. See also is_... | pandas.reference.api.pandas.datetimeindex.is_year_start |
pandas.DatetimeIndex.mean DatetimeIndex.mean(*args, **kwargs)[source]
Return the mean value of the Array. New in version 0.25.0. Parameters
skipna:bool, default True
Whether to ignore any NaT elements.
axis:int, optional, default 0
Returns
scalar
Timestamp or Timedelta. See also numpy.ndarray.... | pandas.reference.api.pandas.datetimeindex.mean |
pandas.DatetimeIndex.microsecond propertyDatetimeIndex.microsecond
The microseconds of the datetime. Examples
>>> datetime_series = pd.Series(
... pd.date_range("2000-01-01", periods=3, freq="us")
... )
>>> datetime_series
0 2000-01-01 00:00:00.000000
1 2000-01-01 00:00:00.000001
2 2000-01-01 00:00:00.00... | pandas.reference.api.pandas.datetimeindex.microsecond |
pandas.DatetimeIndex.minute propertyDatetimeIndex.minute
The minutes of the datetime. Examples
>>> datetime_series = pd.Series(
... pd.date_range("2000-01-01", periods=3, freq="T")
... )
>>> datetime_series
0 2000-01-01 00:00:00
1 2000-01-01 00:01:00
2 2000-01-01 00:02:00
dtype: datetime64[ns]
>>> dateti... | pandas.reference.api.pandas.datetimeindex.minute |
pandas.DatetimeIndex.month propertyDatetimeIndex.month
The month as January=1, December=12. Examples
>>> datetime_series = pd.Series(
... pd.date_range("2000-01-01", periods=3, freq="M")
... )
>>> datetime_series
0 2000-01-31
1 2000-02-29
2 2000-03-31
dtype: datetime64[ns]
>>> datetime_series.dt.month
0 ... | pandas.reference.api.pandas.datetimeindex.month |
pandas.DatetimeIndex.month_name DatetimeIndex.month_name(*args, **kwargs)[source]
Return the month names of the DateTimeIndex with specified locale. Parameters
locale:str, optional
Locale determining the language in which to return the month name. Default is English locale. Returns
Index
Index of month ... | pandas.reference.api.pandas.datetimeindex.month_name |
pandas.DatetimeIndex.nanosecond propertyDatetimeIndex.nanosecond
The nanoseconds of the datetime. Examples
>>> datetime_series = pd.Series(
... pd.date_range("2000-01-01", periods=3, freq="ns")
... )
>>> datetime_series
0 2000-01-01 00:00:00.000000000
1 2000-01-01 00:00:00.000000001
2 2000-01-01 00:00:00... | pandas.reference.api.pandas.datetimeindex.nanosecond |
pandas.DatetimeIndex.normalize DatetimeIndex.normalize(*args, **kwargs)[source]
Convert times to midnight. The time component of the date-time is converted to midnight i.e. 00:00:00. This is useful in cases, when the time does not matter. Length is unaltered. The timezones are unaffected. This method is available o... | pandas.reference.api.pandas.datetimeindex.normalize |
pandas.DatetimeIndex.quarter propertyDatetimeIndex.quarter
The quarter of the date. | pandas.reference.api.pandas.datetimeindex.quarter |
pandas.DatetimeIndex.round DatetimeIndex.round(*args, **kwargs)[source]
Perform round operation on the data to the specified freq. Parameters
freq:str or Offset
The frequency level to round the index to. Must be a fixed frequency like ‘S’ (second) not ‘ME’ (month end). See frequency aliases for a list of poss... | pandas.reference.api.pandas.datetimeindex.round |
pandas.DatetimeIndex.second propertyDatetimeIndex.second
The seconds of the datetime. Examples
>>> datetime_series = pd.Series(
... pd.date_range("2000-01-01", periods=3, freq="s")
... )
>>> datetime_series
0 2000-01-01 00:00:00
1 2000-01-01 00:00:01
2 2000-01-01 00:00:02
dtype: datetime64[ns]
>>> dateti... | pandas.reference.api.pandas.datetimeindex.second |
pandas.DatetimeIndex.snap DatetimeIndex.snap(freq='S')[source]
Snap time stamps to nearest occurring frequency. Returns
DatetimeIndex | pandas.reference.api.pandas.datetimeindex.snap |
pandas.DatetimeIndex.std DatetimeIndex.std(*args, **kwargs)[source]
Return sample standard deviation over requested axis. Normalized by N-1 by default. This can be changed using the ddof argument Parameters
axis:int optional, default None
Axis for the function to be applied on.
ddof:int, default 1
Degrees... | pandas.reference.api.pandas.datetimeindex.std |
pandas.DatetimeIndex.strftime DatetimeIndex.strftime(*args, **kwargs)[source]
Convert to Index using specified date_format. Return an Index of formatted strings specified by date_format, which supports the same string format as the python standard library. Details of the string format can be found in python string ... | pandas.reference.api.pandas.datetimeindex.strftime |
pandas.DatetimeIndex.time propertyDatetimeIndex.time
Returns numpy array of datetime.time objects. The time part of the Timestamps. | pandas.reference.api.pandas.datetimeindex.time |
pandas.DatetimeIndex.timetz propertyDatetimeIndex.timetz
Returns numpy array of datetime.time objects with timezone information. The time part of the Timestamps. | pandas.reference.api.pandas.datetimeindex.timetz |
pandas.DatetimeIndex.to_frame DatetimeIndex.to_frame(index=True, name=NoDefault.no_default)[source]
Create a DataFrame with a column containing the Index. Parameters
index:bool, default True
Set the index of the returned DataFrame as the original Index.
name:object, default None
The passed name should sub... | pandas.reference.api.pandas.datetimeindex.to_frame |
pandas.DatetimeIndex.to_period DatetimeIndex.to_period(*args, **kwargs)[source]
Cast to PeriodArray/Index at a particular frequency. Converts DatetimeArray/Index to PeriodArray/Index. Parameters
freq:str or Offset, optional
One of pandas’ offset strings or an Offset object. Will be inferred by default. Ret... | pandas.reference.api.pandas.datetimeindex.to_period |
pandas.DatetimeIndex.to_perioddelta DatetimeIndex.to_perioddelta(freq)[source]
Calculate TimedeltaArray of difference between index values and index converted to PeriodArray at specified freq. Used for vectorized offsets. Parameters
freq:Period frequency
Returns
TimedeltaArray/Index | pandas.reference.api.pandas.datetimeindex.to_perioddelta |
pandas.DatetimeIndex.to_pydatetime DatetimeIndex.to_pydatetime(*args, **kwargs)[source]
Return Datetime Array/Index as object ndarray of datetime.datetime objects. Returns
datetimes:ndarray[object] | pandas.reference.api.pandas.datetimeindex.to_pydatetime |
pandas.DatetimeIndex.to_series DatetimeIndex.to_series(keep_tz=NoDefault.no_default, index=None, name=None)[source]
Create a Series with both index and values equal to the index keys useful with map for returning an indexer based on an index. Parameters
keep_tz:optional, defaults True
Return the data keeping ... | pandas.reference.api.pandas.datetimeindex.to_series |
pandas.DatetimeIndex.tz propertyDatetimeIndex.tz
Return the timezone. Returns
datetime.tzinfo, pytz.tzinfo.BaseTZInfo, dateutil.tz.tz.tzfile, or None
Returns None when the array is tz-naive. | pandas.reference.api.pandas.datetimeindex.tz |
pandas.DatetimeIndex.tz_convert DatetimeIndex.tz_convert(tz)[source]
Convert tz-aware Datetime Array/Index from one time zone to another. Parameters
tz:str, pytz.timezone, dateutil.tz.tzfile or None
Time zone for time. Corresponding timestamps would be converted to this time zone of the Datetime Array/Index. ... | pandas.reference.api.pandas.datetimeindex.tz_convert |
pandas.DatetimeIndex.tz_localize DatetimeIndex.tz_localize(tz, ambiguous='raise', nonexistent='raise')[source]
Localize tz-naive Datetime Array/Index to tz-aware Datetime Array/Index. This method takes a time zone (tz) naive Datetime Array/Index object and makes this time zone aware. It does not move the time to an... | pandas.reference.api.pandas.datetimeindex.tz_localize |
pandas.DatetimeIndex.week propertyDatetimeIndex.week
The week ordinal of the year. Deprecated since version 1.1.0. weekofyear and week have been deprecated. Please use DatetimeIndex.isocalendar().week instead. | pandas.reference.api.pandas.datetimeindex.week |
pandas.DatetimeIndex.weekday propertyDatetimeIndex.weekday
The day of the week with Monday=0, Sunday=6. Return the day of the week. It is assumed the week starts on Monday, which is denoted by 0 and ends on Sunday which is denoted by 6. This method is available on both Series with datetime values (using the dt acce... | pandas.reference.api.pandas.datetimeindex.weekday |
pandas.DatetimeIndex.weekofyear propertyDatetimeIndex.weekofyear
The week ordinal of the year. Deprecated since version 1.1.0. weekofyear and week have been deprecated. Please use DatetimeIndex.isocalendar().week instead. | pandas.reference.api.pandas.datetimeindex.weekofyear |
pandas.DatetimeIndex.year propertyDatetimeIndex.year
The year of the datetime. Examples
>>> datetime_series = pd.Series(
... pd.date_range("2000-01-01", periods=3, freq="Y")
... )
>>> datetime_series
0 2000-12-31
1 2001-12-31
2 2002-12-31
dtype: datetime64[ns]
>>> datetime_series.dt.year
0 2000
1 2... | pandas.reference.api.pandas.datetimeindex.year |
pandas.DatetimeTZDtype classpandas.DatetimeTZDtype(unit='ns', tz=None)[source]
An ExtensionDtype for timezone-aware datetime data. This is not an actual numpy dtype, but a duck type. Parameters
unit:str, default “ns”
The precision of the datetime data. Currently limited to "ns".
tz:str, int, or datetime.tzi... | pandas.reference.api.pandas.datetimetzdtype |
pandas.DatetimeTZDtype.tz propertyDatetimeTZDtype.tz
The timezone. | pandas.reference.api.pandas.datetimetzdtype.tz |
pandas.DatetimeTZDtype.unit propertyDatetimeTZDtype.unit
The precision of the datetime data. | pandas.reference.api.pandas.datetimetzdtype.unit |
pandas.describe_option pandas.describe_option(pat, _print_desc=False)=<pandas._config.config.CallableDynamicDoc object>
Prints the description for one or more registered options. Call with no arguments to get a listing for all registered options. Available options: compute.[use_bottleneck, use_numba, use_numexpr] ... | pandas.reference.api.pandas.describe_option |
pandas.errors.AbstractMethodError exceptionpandas.errors.AbstractMethodError(class_instance, methodtype='method')[source]
Raise this error instead of NotImplementedError for abstract methods while keeping compatibility with Python 2 and Python 3. | pandas.reference.api.pandas.errors.abstractmethoderror |
pandas.errors.AccessorRegistrationWarning exceptionpandas.errors.AccessorRegistrationWarning[source]
Warning for attribute conflicts in accessor registration. | pandas.reference.api.pandas.errors.accessorregistrationwarning |
pandas.errors.DtypeWarning exceptionpandas.errors.DtypeWarning[source]
Warning raised when reading different dtypes in a column from a file. Raised for a dtype incompatibility. This can happen whenever read_csv or read_table encounter non-uniform dtypes in a column(s) of a given CSV file. See also read_csv
Read ... | pandas.reference.api.pandas.errors.dtypewarning |
pandas.errors.DuplicateLabelError exceptionpandas.errors.DuplicateLabelError[source]
Error raised when an operation would introduce duplicate labels. New in version 1.2.0. Examples
>>> s = pd.Series([0, 1, 2], index=['a', 'b', 'c']).set_flags(
... allows_duplicate_labels=False
... )
>>> s.reindex(['a', 'a', ... | pandas.reference.api.pandas.errors.duplicatelabelerror |
pandas.errors.EmptyDataError exceptionpandas.errors.EmptyDataError[source]
Exception that is thrown in pd.read_csv (by both the C and Python engines) when empty data or header is encountered. | pandas.reference.api.pandas.errors.emptydataerror |
pandas.errors.IntCastingNaNError exceptionpandas.errors.IntCastingNaNError[source]
Raised when attempting an astype operation on an array with NaN to an integer dtype. | pandas.reference.api.pandas.errors.intcastingnanerror |
pandas.errors.InvalidIndexError exceptionpandas.errors.InvalidIndexError[source]
Exception raised when attempting to use an invalid index key. New in version 1.1.0. | pandas.reference.api.pandas.errors.invalidindexerror |
pandas.errors.MergeError exceptionpandas.errors.MergeError[source]
Error raised when problems arise during merging due to problems with input data. Subclass of ValueError. | pandas.reference.api.pandas.errors.mergeerror |
pandas.errors.NullFrequencyError exceptionpandas.errors.NullFrequencyError[source]
Error raised when a null freq attribute is used in an operation that needs a non-null frequency, particularly DatetimeIndex.shift, TimedeltaIndex.shift, PeriodIndex.shift. | pandas.reference.api.pandas.errors.nullfrequencyerror |
pandas.errors.NumbaUtilError exceptionpandas.errors.NumbaUtilError[source]
Error raised for unsupported Numba engine routines. | pandas.reference.api.pandas.errors.numbautilerror |
pandas.errors.OptionError exceptionpandas.errors.OptionError[source]
Exception for pandas.options, backwards compatible with KeyError checks. | pandas.reference.api.pandas.errors.optionerror |
pandas.errors.OutOfBoundsDatetime exceptionpandas.errors.OutOfBoundsDatetime | pandas.reference.api.pandas.errors.outofboundsdatetime |
pandas.errors.OutOfBoundsTimedelta exceptionpandas.errors.OutOfBoundsTimedelta
Raised when encountering a timedelta value that cannot be represented as a timedelta64[ns]. | pandas.reference.api.pandas.errors.outofboundstimedelta |
pandas.errors.ParserError exceptionpandas.errors.ParserError[source]
Exception that is raised by an error encountered in parsing file contents. This is a generic error raised for errors encountered when functions like read_csv or read_html are parsing contents of a file. See also read_csv
Read CSV (comma-separat... | pandas.reference.api.pandas.errors.parsererror |
pandas.errors.ParserWarning exceptionpandas.errors.ParserWarning[source]
Warning raised when reading a file that doesn’t use the default ‘c’ parser. Raised by pd.read_csv and pd.read_table when it is necessary to change parsers, generally from the default ‘c’ parser to ‘python’. It happens due to a lack of support ... | pandas.reference.api.pandas.errors.parserwarning |
pandas.errors.PerformanceWarning exceptionpandas.errors.PerformanceWarning[source]
Warning raised when there is a possible performance impact. | pandas.reference.api.pandas.errors.performancewarning |
pandas.errors.UnsortedIndexError exceptionpandas.errors.UnsortedIndexError[source]
Error raised when attempting to get a slice of a MultiIndex, and the index has not been lexsorted. Subclass of KeyError. | pandas.reference.api.pandas.errors.unsortedindexerror |
pandas.errors.UnsupportedFunctionCall exceptionpandas.errors.UnsupportedFunctionCall[source]
Exception raised when attempting to call a numpy function on a pandas object, but that function is not supported by the object e.g. np.cumsum(groupby_object). | pandas.reference.api.pandas.errors.unsupportedfunctioncall |
pandas.eval pandas.eval(expr, parser='pandas', engine=None, truediv=NoDefault.no_default, local_dict=None, global_dict=None, resolvers=(), level=0, target=None, inplace=False)[source]
Evaluate a Python expression as a string using various backends. The following arithmetic operations are supported: +, -, *, /, **, ... | pandas.reference.api.pandas.eval |
pandas.ExcelFile.parse ExcelFile.parse(sheet_name=0, header=0, names=None, index_col=None, usecols=None, squeeze=None, converters=None, true_values=None, false_values=None, skiprows=None, nrows=None, na_values=None, parse_dates=False, date_parser=None, thousands=None, comment=None, skipfooter=0, convert_float=None, m... | pandas.reference.api.pandas.excelfile.parse |
pandas.ExcelWriter classpandas.ExcelWriter(path, engine=None, date_format=None, datetime_format=None, mode='w', storage_options=None, if_sheet_exists=None, engine_kwargs=None, **kwargs)[source]
Class for writing DataFrame objects into excel sheets. Default is to use : * xlwt for xls * xlsxwriter for xlsx if xlsxwri... | pandas.reference.api.pandas.excelwriter |
pandas.factorize pandas.factorize(values, sort=False, na_sentinel=- 1, size_hint=None)[source]
Encode the object as an enumerated type or categorical variable. This method is useful for obtaining a numeric representation of an array when all that matters is identifying distinct values. factorize is available as bot... | pandas.reference.api.pandas.factorize |
pandas.Flags classpandas.Flags(obj, *, allows_duplicate_labels)[source]
Flags that apply to pandas objects. New in version 1.2.0. Parameters
obj:Series or DataFrame
The object these flags are associated with.
allows_duplicate_labels:bool, default True
Whether to allow duplicate labels in this object. By... | pandas.reference.api.pandas.flags |
pandas.Flags.allows_duplicate_labels propertyFlags.allows_duplicate_labels
Whether this object allows duplicate labels. Setting allows_duplicate_labels=False ensures that the index (and columns of a DataFrame) are unique. Most methods that accept and return a Series or DataFrame will propagate the value of allows_d... | pandas.reference.api.pandas.flags.allows_duplicate_labels |
pandas.Float64Index classpandas.Float64Index(data=None, dtype=None, copy=False, name=None)[source]
Immutable sequence used for indexing and alignment. The basic object storing axis labels for all pandas objects. Float64Index is a special case of Index with purely float labels. . Deprecated since version 1.4.0: In ... | pandas.reference.api.pandas.float64index |
pandas.get_dummies pandas.get_dummies(data, prefix=None, prefix_sep='_', dummy_na=False, columns=None, sparse=False, drop_first=False, dtype=None)[source]
Convert categorical variable into dummy/indicator variables. Parameters
data:array-like, Series, or DataFrame
Data of which to get dummy indicators.
pref... | pandas.reference.api.pandas.get_dummies |
pandas.get_option pandas.get_option(pat)=<pandas._config.config.CallableDynamicDoc object>
Retrieves the value of the specified option. Available options: compute.[use_bottleneck, use_numba, use_numexpr] display.[chop_threshold, colheader_justify, column_space, date_dayfirst, date_yearfirst, encoding, expand_frame... | pandas.reference.api.pandas.get_option |
pandas.Grouper classpandas.Grouper(*args, **kwargs)[source]
A Grouper allows the user to specify a groupby instruction for an object. This specification will select a column via the key parameter, or if the level and/or axis parameters are given, a level of the index of the target object. If axis and/or level are p... | pandas.reference.api.pandas.grouper |
pandas.HDFStore.append HDFStore.append(key, value, format=None, axes=None, index=True, append=True, complib=None, complevel=None, columns=None, min_itemsize=None, nan_rep=None, chunksize=None, expectedrows=None, dropna=None, data_columns=None, encoding=None, errors='strict')[source]
Append to Table in file. Node mu... | pandas.reference.api.pandas.hdfstore.append |
pandas.HDFStore.get HDFStore.get(key)[source]
Retrieve pandas object stored in file. Parameters
key:str
Returns
object
Same type as object stored in file. | pandas.reference.api.pandas.hdfstore.get |
pandas.HDFStore.groups HDFStore.groups()[source]
Return a list of all the top-level nodes. Each node returned is not a pandas storage object. Returns
list
List of objects. | pandas.reference.api.pandas.hdfstore.groups |
pandas.HDFStore.info HDFStore.info()[source]
Print detailed information on the store. Returns
str | pandas.reference.api.pandas.hdfstore.info |
pandas.HDFStore.keys HDFStore.keys(include='pandas')[source]
Return a list of keys corresponding to objects stored in HDFStore. Parameters
include:str, default ‘pandas’
When kind equals ‘pandas’ return pandas objects. When kind equals ‘native’ return native HDF5 Table objects. New in version 1.1.0. Retur... | pandas.reference.api.pandas.hdfstore.keys |
pandas.HDFStore.put HDFStore.put(key, value, format=None, index=True, append=False, complib=None, complevel=None, min_itemsize=None, nan_rep=None, data_columns=None, encoding=None, errors='strict', track_times=True, dropna=False)[source]
Store object in HDFStore. Parameters
key:str
value:{Series, DataFrame}
... | pandas.reference.api.pandas.hdfstore.put |
pandas.HDFStore.select HDFStore.select(key, where=None, start=None, stop=None, columns=None, iterator=False, chunksize=None, auto_close=False)[source]
Retrieve pandas object stored in file, optionally based on where criteria. Warning Pandas uses PyTables for reading and writing HDF5 files, which allows serializing... | pandas.reference.api.pandas.hdfstore.select |
pandas.HDFStore.walk HDFStore.walk(where='/')[source]
Walk the pytables group hierarchy for pandas objects. This generator will yield the group path, subgroups and pandas object names for each group. Any non-pandas PyTables objects that are not a group will be ignored. The where group itself is listed first (preord... | pandas.reference.api.pandas.hdfstore.walk |
pandas.Index classpandas.Index(data=None, dtype=None, copy=False, name=None, tupleize_cols=True, **kwargs)[source]
Immutable sequence used for indexing and alignment. The basic object storing axis labels for all pandas objects. Parameters
data:array-like (1-dimensional)
dtype:NumPy dtype (default: object)
I... | pandas.reference.api.pandas.index |
pandas.Index.all Index.all(*args, **kwargs)[source]
Return whether all elements are Truthy. Parameters
*args
Required for compatibility with numpy. **kwargs
Required for compatibility with numpy. Returns
all:bool or array-like (if axis is specified)
A single element array-like may be converted to bool... | pandas.reference.api.pandas.index.all |
pandas.Index.any Index.any(*args, **kwargs)[source]
Return whether any element is Truthy. Parameters
*args
Required for compatibility with numpy. **kwargs
Required for compatibility with numpy. Returns
any:bool or array-like (if axis is specified)
A single element array-like may be converted to bool. ... | pandas.reference.api.pandas.index.any |
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