Pandas._frame — Pandas 1.4.3 Documentation
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- Series
- pandas.Series
- pandas.Series.index
- pandas.Series.array
- pandas.Series.values
- pandas.Series.dtype
- pandas.Series.info
- pandas.Series.shape
- pandas.Series.nbytes
- pandas.Series.ndim
- pandas.Series.size
- pandas.Series.T
- pandas.Series.memory_usage
- pandas.Series.hasnans
- pandas.Series.empty
- pandas.Series.dtypes
- pandas.Series.name
- pandas.Series.flags
- pandas.Series.set_flags
- pandas.Series.astype
- pandas.Series.convert_dtypes
- pandas.Series.infer_objects
- pandas.Series.copy
- pandas.Series.to_numpy
- pandas.Series.to_period
- pandas.Series.to_timestamp
- pandas.Series.to_list
- pandas.Series.__array__
- pandas.Series.get
- pandas.Series.at
- pandas.Series.iat
- pandas.Series.loc
- pandas.Series.iloc
- pandas.Series.__iter__
- pandas.Series.items
- pandas.Series.keys
- pandas.Series.pop
- pandas.Series.item
- pandas.Series.xs
- pandas.Series.add
- pandas.Series.sub
- pandas.Series.mul
- pandas.Series.div
- pandas.Series.divmod
- pandas.Series.truediv
- pandas.Series.floordiv
- pandas.Series.mod
- pandas.Series.pow
- pandas.Series.radd
- pandas.Series.rsub
- pandas.Series.rmul
- pandas.Series.rdiv
- pandas.Series.rdivmod
- pandas.Series.rtruediv
- pandas.Series.rfloordiv
- pandas.Series.rmod
- pandas.Series.rpow
- pandas.Series.combine
- pandas.Series.combine_first
- pandas.Series.round
- pandas.Series.lt
- pandas.Series.gt
- pandas.Series.le
- pandas.Series.ge
- pandas.Series.ne
- pandas.Series.eq
- pandas.Series.product
- pandas.Series.dot
- pandas.Series.apply
- pandas.Series.agg
- pandas.Series.aggregate
- pandas.Series.transform
- pandas.Series.map
- pandas.Series.groupby
- pandas.Series.rolling
- pandas.Series.expanding
- pandas.Series.ewm
- pandas.Series.pipe
- pandas.Series.abs
- pandas.Series.all
- pandas.Series.any
- pandas.Series.autocorr
- pandas.Series.between
- pandas.Series.clip
- pandas.Series.corr
- pandas.Series.count
- pandas.Series.cov
- pandas.Series.cummax
- pandas.Series.cummin
- pandas.Series.cumprod
- pandas.Series.cumsum
- pandas.Series.describe
- pandas.Series.diff
- pandas.Series.factorize
- pandas.Series.kurt
- pandas.Series.max
- pandas.Series.mean
- pandas.Series.median
- pandas.Series.min
- pandas.Series.mode
- pandas.Series.nlargest
- pandas.Series.nsmallest
- pandas.Series.pct_change
- pandas.Series.prod
- pandas.Series.quantile
- pandas.Series.rank
- pandas.Series.sem
- pandas.Series.skew
- pandas.Series.std
- pandas.Series.sum
- pandas.Series.var
- pandas.Series.kurtosis
- pandas.Series.unique
- pandas.Series.nunique
- pandas.Series.is_unique
- pandas.Series.is_monotonic_increasing
- pandas.Series.is_monotonic_decreasing
- pandas.Series.value_counts
- pandas.Series.align
- pandas.Series.case_when
- pandas.Series.drop
- pandas.Series.droplevel
- pandas.Series.drop_duplicates
- pandas.Series.duplicated
- pandas.Series.equals
- pandas.Series.head
- pandas.Series.idxmax
- pandas.Series.idxmin
- pandas.Series.isin
- pandas.Series.reindex
- pandas.Series.reindex_like
- pandas.Series.rename
- pandas.Series.rename_axis
- pandas.Series.reset_index
- pandas.Series.sample
- pandas.Series.set_axis
- pandas.Series.take
- pandas.Series.tail
- pandas.Series.truncate
- pandas.Series.where
- pandas.Series.mask
- pandas.Series.add_prefix
- pandas.Series.add_suffix
- pandas.Series.filter
- pandas.Series.bfill
- pandas.Series.dropna
- pandas.Series.ffill
- pandas.Series.fillna
- pandas.Series.interpolate
- pandas.Series.isna
- pandas.Series.isnull
- pandas.Series.notna
- pandas.Series.notnull
- pandas.Series.replace
- pandas.Series.argsort
- pandas.Series.argmin
- pandas.Series.argmax
- pandas.Series.reorder_levels
- pandas.Series.sort_values
- pandas.Series.sort_index
- pandas.Series.swaplevel
- pandas.Series.unstack
- pandas.Series.explode
- pandas.Series.searchsorted
- pandas.Series.repeat
- pandas.Series.squeeze
- pandas.Series.compare
- pandas.Series.update
- pandas.Series.asfreq
- pandas.Series.asof
- pandas.Series.shift
- pandas.Series.first_valid_index
- pandas.Series.last_valid_index
- pandas.Series.resample
- pandas.Series.tz_convert
- pandas.Series.tz_localize
- pandas.Series.at_time
- pandas.Series.between_time
- pandas.Series.str
- pandas.Series.cat
- pandas.Series.dt
- pandas.Series.sparse
- pandas.DataFrame.sparse
- pandas.Index.str
- pandas.Series.dt.date
- pandas.Series.dt.time
- pandas.Series.dt.timetz
- pandas.Series.dt.year
- pandas.Series.dt.month
- pandas.Series.dt.day
- pandas.Series.dt.hour
- pandas.Series.dt.minute
- pandas.Series.dt.second
- pandas.Series.dt.microsecond
- pandas.Series.dt.nanosecond
- pandas.Series.dt.dayofweek
- pandas.Series.dt.day_of_week
- pandas.Series.dt.weekday
- pandas.Series.dt.dayofyear
- pandas.Series.dt.day_of_year
- pandas.Series.dt.days_in_month
- pandas.Series.dt.quarter
- pandas.Series.dt.is_month_start
- pandas.Series.dt.is_month_end
- pandas.Series.dt.is_quarter_start
- pandas.Series.dt.is_quarter_end
- pandas.Series.dt.is_year_start
- pandas.Series.dt.is_year_end
- pandas.Series.dt.is_leap_year
- pandas.Series.dt.daysinmonth
- pandas.Series.dt.days_in_month
- pandas.Series.dt.tz
- pandas.Series.dt.freq
- pandas.Series.dt.unit
- pandas.Series.dt.isocalendar
- pandas.Series.dt.to_period
- pandas.Series.dt.to_pydatetime
- pandas.Series.dt.tz_localize
- pandas.Series.dt.tz_convert
- pandas.Series.dt.normalize
- pandas.Series.dt.strftime
- pandas.Series.dt.round
- pandas.Series.dt.floor
- pandas.Series.dt.ceil
- pandas.Series.dt.month_name
- pandas.Series.dt.day_name
- pandas.Series.dt.as_unit
- pandas.Series.dt.qyear
- pandas.Series.dt.start_time
- pandas.Series.dt.end_time
- pandas.Series.dt.days
- pandas.Series.dt.seconds
- pandas.Series.dt.microseconds
- pandas.Series.dt.nanoseconds
- pandas.Series.dt.components
- pandas.Series.dt.unit
- pandas.Series.dt.to_pytimedelta
- pandas.Series.dt.total_seconds
- pandas.Series.dt.as_unit
- pandas.Series.str.capitalize
- pandas.Series.str.casefold
- pandas.Series.str.cat
- pandas.Series.str.center
- pandas.Series.str.contains
- pandas.Series.str.count
- pandas.Series.str.decode
- pandas.Series.str.encode
- pandas.Series.str.endswith
- pandas.Series.str.extract
- pandas.Series.str.extractall
- pandas.Series.str.find
- pandas.Series.str.findall
- pandas.Series.str.fullmatch
- pandas.Series.str.get
- pandas.Series.str.index
- pandas.Series.str.isascii
- pandas.Series.str.join
- pandas.Series.str.len
- pandas.Series.str.ljust
- pandas.Series.str.lower
- pandas.Series.str.lstrip
- pandas.Series.str.match
- pandas.Series.str.normalize
- pandas.Series.str.pad
- pandas.Series.str.partition
- pandas.Series.str.removeprefix
- pandas.Series.str.removesuffix
- pandas.Series.str.repeat
- pandas.Series.str.replace
- pandas.Series.str.rfind
- pandas.Series.str.rindex
- pandas.Series.str.rjust
- pandas.Series.str.rpartition
- pandas.Series.str.rstrip
- pandas.Series.str.slice
- pandas.Series.str.slice_replace
- pandas.Series.str.split
- pandas.Series.str.rsplit
- pandas.Series.str.startswith
- pandas.Series.str.strip
- pandas.Series.str.swapcase
- pandas.Series.str.title
- pandas.Series.str.translate
- pandas.Series.str.upper
- pandas.Series.str.wrap
- pandas.Series.str.zfill
- pandas.Series.str.isalnum
- pandas.Series.str.isalpha
- pandas.Series.str.isdigit
- pandas.Series.str.isspace
- pandas.Series.str.islower
- pandas.Series.str.isupper
- pandas.Series.str.istitle
- pandas.Series.str.isnumeric
- pandas.Series.str.isdecimal
- pandas.Series.str.get_dummies
- pandas.Series.cat.categories
- pandas.Series.cat.ordered
- pandas.Series.cat.codes
- pandas.Series.cat.rename_categories
- pandas.Series.cat.reorder_categories
- pandas.Series.cat.add_categories
- pandas.Series.cat.remove_categories
- pandas.Series.cat.remove_unused_categories
- pandas.Series.cat.set_categories
- pandas.Series.cat.as_ordered
- pandas.Series.cat.as_unordered
- pandas.Series.sparse.npoints
- pandas.Series.sparse.density
- pandas.Series.sparse.fill_value
- pandas.Series.sparse.sp_values
- pandas.Series.sparse.from_coo
- pandas.Series.sparse.to_coo
- pandas.Series.list.flatten
- pandas.Series.list.len
- pandas.Series.list.__getitem__
- pandas.Series.struct.dtypes
- pandas.Series.struct.field
- pandas.Series.struct.explode
- pandas.Flags
- pandas.Series.attrs
- pandas.Series.plot
- pandas.Series.plot.area
- pandas.Series.plot.bar
- pandas.Series.plot.barh
- pandas.Series.plot.box
- pandas.Series.plot.density
- pandas.Series.plot.hist
- pandas.Series.plot.kde
- pandas.Series.plot.line
- pandas.Series.plot.pie
- pandas.Series.hist
- pandas.Series.from_arrow
- pandas.Series.to_pickle
- pandas.Series.to_csv
- pandas.Series.to_dict
- pandas.Series.to_excel
- pandas.Series.to_frame
- pandas.Series.to_xarray
- pandas.Series.to_hdf
- pandas.Series.to_sql
- pandas.Series.to_json
- pandas.Series.to_string
- pandas.Series.to_clipboard
- pandas.Series.to_latex
- pandas.Series.to_markdown
- DataFrame
- pandas arrays, scalars, and data types
- Index objects
- Date offsets
- Window
- GroupBy
- Resampling
- Style
- Plotting
- Options and settings
- Extensions
- Testing
- Missing values
- pandas typing aliases
- API reference
- Series
- pandas.Series.to_frame
Convert Series to DataFrame.
The resulting DataFrame contains a single column. The name of the column can be set using the name parameter; otherwise it defaults to the Series’ name.
Parameters: nameobject, optionalThe passed name should substitute for the series name (if it has one).
Returns: DataFrameDataFrame representation of Series.
See also
Series.to_dictConvert Series to dict object.
Examples
>>> s = pd.Series(["a", "b", "c"], name="vals") >>> s.to_frame() vals 0 a 1 b 2 c On this page- Series.to_frame()
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