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MIN
MODE
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NTILE
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IFF
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CEILING
CONV
COS
COTAN
DEGREES
EXP
FLOOR
GETBIT
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LN
LOG
LOG10
MOD
PI
POWER
RADIANS
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SIGN
SIN
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TAN
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Object Functions
Object Functions
GET_PATH
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BASE64_DECODE_BINARY
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LENGTH
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ORD
POSITION
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RIGHT
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SHA2_HEX
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STRTOK
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ADDDATE
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DATEDIFF
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FROM_DAYS
FROM_UNIXTIME
GETDATE
HOUR
LAST_DAY
LOCALTIME
LOCALTIMESTAMP
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MICROSECOND
MINUTE
MONTH
MONTH_NAME
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NOW
QUARTER
SECOND
STR_TO_DATE
SUBDATE
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TIME_FROM_PARTS
TIME_SLICE
TIMEADD
TIMEFROMPARTS
TIMESTAMP_FROM_PARTS
TIMESTAMP_LTZ_FROM_PARTS
TIMESTAMP_NTZ_FROM_PARTS
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TIMESTAMPADD
TIMESTAMPDIFF
TIMESTAMPFROMPARTS
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TO_DAYS
TO_SECONDS
TRUNC
UNIX_TIMESTAMP
UTC_DATE
UTC_TIMESTAMP
WEEK
WEEKDAY
WEEKISO
WEEKOFYEAR
YEAR
YEAROFWEEKISO
YEARWEEK
Type Predicates
Type Predicates
IS_ARRAY
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Bodo Parallel API Reference
Bodo Parallel API Reference
bodo.allgatherv
bodo.barrier
bodo.gatherv
bodo.get_rank
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Python Reference
Python Reference
Pandas
Pandas
General Functions
General Functions
pd.crosstab
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pd.to_timedelta
pd.date_range
pd.timedelta_range
DataFrame
DataFrame
pd.Dataframe
pd.DataFrame.abs
pd.DataFrame.append
pd.DataFrame.apply
pd.DataFrame.assign
pd.DataFrame.astype
pd.DataFrame.columns
pd.DataFrame.copy
pd.DataFrame.corr
pd.DataFrame.count
pd.DataFrame.cov
pd.DataFrame.cumprod
pd.DataFrame.cumsum
pd.DataFrame
pd.DataFrame.describe
pd.DataFrame.index
pd.DataFrame.diff
pd.DataFrame.drop
pd.DataFrame.drop_duplicates
pd.DataFrame.dropna
pd.DataFrame.dtypes
pd.DataFrame.duplicated
pd.DataFrame.empty
pd.DataFrame.explode
pd.DataFrame.fillna
pd.DataFrame.filter
pd.DataFrame.first
pd.DataFrame.groupby
pd.DataFrame.head
pd.DataFrame.iat
pd.DataFrame.idxmax
pd.DataFrame.idxmin
pd.DataFrame.iloc
DataFrame
pd.DataFrame.infer_objects
pd.DataFrame.info
pd.DataFrame.insert
pd.DataFrame.isin
pd.DataFrame.isna
pd.DataFrame.isnull
pd.DataFrame.itertuples
pd.DataFrame.join
pd.DataFrame.last
pd.DataFrame.mask
pd.DataFrame.max
pd.DataFrame.mean
pd.DataFrame.median
pd.DataFrame.melt
pd.DataFrame.memory_usage
pd.DataFrame.merge
pd.DataFrame.min
pd.DataFrame.ndim
pd.DataFrame.notna
pd.DataFrame.notnull
pd.DataFrame.nunique
pd.DataFrame.pct_change
pd.DataFrame.pipe
pd.DataFrame.pivot
pd.DataFrame.pivot_table
pd.DataFrame.plot
pd.DataFrame.prod
pd.DataFrame.product
pd.DataFrame.quantile
pd.DataFrame.query
pd.DataFrame.rank
pd.DataFrame.rename
pd.DataFrame.replace
pd.DataFrame.reset_index
pd.DataFrame.rolling
pd.DataFrame.sample
pd.DataFrame.select_dtypes
pd.DataFrame.set_index
pd.DataFrame.shape
pd.DataFrame.shift
pd.DataFrame.size
pd.DataFrame.sort_index
pd.DataFrame.sort_values
pd.DataFrame.std
pd.DataFrame.sum
pd.DataFrame.tail
pd.DataFrame.take
pd.DataFrame.to_csv
pd.DataFrame.to_json
pd.DataFrame.to_numpy
pd.DataFrame.to_parquet
pd.DataFrame.to_sql
pd.DataFrame.to_string
pd.DataFrame.values
pd.DataFrame.var
pd.DataFrame.where
Groupby
Groupby
pd.core.groupby.Groupby.agg
pd.core.groupby.DataFrameGroupby.aggregate
pd.core.groupby.Groupby.apply
pd.core.groupby.Groupby.count
pd.core.groupby.Groupby.cumsum
pd.core.groupby.Groupby.first
pd.DataFrame.groupby
pd.core.groupby.Groupby.head
pd.core.groupby.DataFrameGroupby.idxmax
pd.core.groupby.DataFrameGroupby.idxmin
pd.core.groupby.Groupby.last
pd.core.groupby.Groupby.max
pd.core.groupby.Groupby.mean
pd.core.groupby.Groupby.median
pd.core.groupby.Groupby.min
pd.core.groupby.DataFrameGroupby.nunique
pd.core.groupby.Groupby.pipe
pd.core.groupby.Groupby.prod
pd.core.groupby.Groupby.rolling
pd.Series.groupby
pd.core.groupby.DataFrameGroupby.shift
pd.core.groupby.Groupby.size
pd.core.groupby.Groupby.std
pd.core.groupby.Groupby.sum
pd.core.groupby.DataFrameGroupby.transform
pd.core.groupby.SeriesGroupBy.value_counts
pd.core.groupby.Groupby.var
Series
Series
pd.Series
pd.Series.abs
pd.Series.add
pd.Series.all
pd.Series.any
pd.Series.append
pd.Series.apply
pd.Series.argsort
pd.Series.astype
pd.Series.autocorr
pd.Series.backfill
pd.Series.between
pd.Series.bfill
pd.Series.cat.codes
pd.Series.combine
pd.Series.copy
pd.Series.corr
pd.Series.count
pd.Series.cov
pd.Series.cummax
pd.Series.cummin
pd.Series.cumprod
pd.Series.cumsum
pd.Series.describe
pd.Series.diff
pd.Series.div
pd.Series.dot
pd.Series.drop_duplicates
pd.Series.dropna
pd.Series.dt.ceil
`pd.Series.dt.date
pd.Series.dt.day
pd.Series.dt.day_name
pd.Series.dt.day_of_week
pd.Series.dt.day_of_year
pd.Series.dt.dayofyear
pd.Series.dt.days_in_month
pd.Series.dt.daysinmonth
pd.Series.dt.floor
pd.Series.dt.hour
pd.Series.dt.is_month_end
pd.Series.dt.is_month_start
pd.Series.dt.is_quarter_end
pd.Series.dt.is_quarter_start
pd.Series.dt.is_year_end
pd.Series.dt.is_year_start
pd.Series.dt.microsecond
pd.Series.dt.minute
pd.Series.dt.month
pd.Series.dt.month_name
pd.Series.dt.nanosecond
pd.Series.dt.normalize
pd.Series.dt.quarter
pd.Series.dt.round
pd.Series.dt.second
pd.Series.dt.strftime
pd.Series.dt.week
pd.Series.dt.weekday
pd.Series.dt.weekofyear
pd.Series.dt.year
pd.Series.dtype
pd.Series.dtypes
pd.Series.duplicated
pd.Series.empty
pd.Series.eq
pd.Series.equals
pd.Series.explode
pd.Series.ffill
pd.Series.fillna
pd.Series.first
pd.Series.floordiv
pd.Series.ge
pd.Series.groupby
pd.Series.gt
pd.Series.hasnans
pd.Series.head
pd.Series.iat
pd.Series.idxmax
pd.Series.idxmin
pd.Series.iloc
pd.Series.is_monotonic
pd.Series.is_monotonic_decreasing
pd.Series.is_monotonic_increasing
pd.Series.isin
pd.Series.isna
pd.Series.isnull
pd.Series.kurt
pd.Series.kurtosis
pd.Series.last
pd.Series.le
pd.Series.loc
pd.Series.lt
pd.Series.mad
pd.Series.map
pd.Series.mask
pd.Series.max
pd.Series.mean
pd.Series.median
pd.Series.memory_usage
pd.Series.min
pd.Series.mod
pd.Series.mul
pd.Series.name
pd.Series.nbytes
pd.Series.ndim
pd.Series.ne
pd.Series.nlargest
pd.Series.notna
pd.Series.notnull
pd.Series.nsmallest
pd.Series.nunique
pd.Series.pad
pd.Series.pct_change
pd.Series.pipe
pd.Series.pow
pd.Series.prod
pd.Series.product
pd.Series.quantile
pd.Series.radd
pd.Series.rank
pd.Series.rdiv
pd.Series.rename
pd.Series.repeat
pd.Series.replace
pd.Series.reset_index
pd.Series.rfloordiv
pd.Series.rmod
pd.Series.rmul
pd.Series.rolling
pd.Series.round
pd.Series.rpow
pd.Series.rsub
pd.Series.rtruediv
pd.Series.sem
pd.Series.index
pd.Series.shape
pd.Series.shift
pd.Series.size
pd.Series.skew
pd.Series.sort_index
pd.Series.sort_values
pd.Series.std
pd.Series.str.capitalize
pd.Series.str.cat
pd.Series.str.center
pd.Series.str.contains
pd.Series.str.count
pd.Series.str.endswith
pd.Series.str.extract
pd.Series.str.extractall
pd.Series.str.find
pd.Series.str.get
pd.Series.str.isalnum
pd.Series.str.isalpha
pd.Series.str.isdecimal
pd.Series.str.isdigit
pd.Series.str.islower
pd.Series.str.isnumeric
pd.Series.str.isspace
pd.Series.str.istitle
pd.Series.str.isupper
pd.Series.str.join
pd.Series.str.len
pd.Series.str.ljust
pd.Series.str.lower
pd.Series.str.lstrip
pd.Series.str.pad
pd.Series.str.repeat
pd.Series.str.replace
pd.Series.str.restrip
pd.Series.str.rfind
pd.Series.str.rjist
pd.Series.str.slice
pd.Series.str.slice_replace
pd.Series.str.split
pd.Series.str.startswith
pd.Series.str.strip
pd.Series.str.swapcase
pd.Series.str.title
pd.Series.str.upper
pd.Series.str.zfill
pd.Series.sub
pd.Series.sum
pd.Series.T
pd.Series.tail
pd.Series.take
pd.Series.to_csv
pd.Series.to_dict
pd.Series.to_frame
pd.Series.to_numpy
pd.Series.tolist
pd.Series.truediv
pd.Series.unique
pd.Series.value_counts
pd.Series.values
pd.Series.var
pd.Series.where
Window
Window
pd.core.window.rolling.Rolling.apply
pd.core.window.rolling.Rolling.corr
pd.core.window.rolling.Rolling.count
pd.core.window.rolling.Rolling.cov
pd.core.window.rolling.Rolling.max
pd.core.window.rolling.Rolling.mean
pd.core.window.rolling.Rolling.median
pd.core.window.rolling.Rolling.min
pd.core.window.rolling.Rolling.std
pd.core.window.rolling.Rolling.sum
pd.core.window.rolling.Rolling.var
DateOffsets
DateOffsets
pd.tseries.offsets.DateOffset
pd.tseries.offsets.MonthBegin
pd.tseries.offsets.MonthEnd
pd.tseries.offsets.DateOffset.n
pd.tseries.offsets.DateOffset.normalize`
pd.tseries.offsets.Week
Input/Output
Input/Output
pd.read_csv
pd.read_excel
pd.read_json
pd.read_parquet
pd.read_sql
pd.read_sql_table
Index Objects
Index Objects
pd.Index.all
pd.Index.any
pd.Index.argmax
pd.Index.argmin
pd.Index.argsort
pd.Index.copy
pd.DateTimeIndex.date
pd.DateTimeIndex
pd.DateTimeIndex.day
pd.DateTimeIndex.day_of_week
pd.DateTimeIndex.day_of_year
pd.DateTimeIndex.dayofweek
pd.DateTimeIndex.dayofyear
pd.TimedeltaIndex.days
pd.Index.difference
pd.Index.drop_duplicates
pd.Index.dtype
pd.Index.duplicated
pd.Index.empty
pd.Float64Index
pd.MultiIndex.from_product
pd.Index.get_loc
pd.DateTimeIndex.hour
pd.Index.inferred_type
pd.Int64Index
pd.Index.intersection
pd.Index.is_all_dates
pd.Index.is_boolean
pd.Index.is_categorical
pd.Index.is_floating
pd.Index.is_integer
pd.Index.is_interval
pd.DateTimeIndex.is_leap_year
pd.Index.is_monotonic_decreasing
pd.Index.is_monotonic_increasing
pd.DateTimeIndex.is_month_end
pd.DateTimeIndex.is_month_start
pd.Index.is_numeric
pd.Index.is_object
pd.DateTimeIndex.is_quarter_end
pd.DateTimeIndex.is_quarter_start
pd.DateTimeIndex.is_year_end
pd.DateTimeIndex.is_year_start
pd.Index.isin
pd.Index.isna
pd.Index.isnull
pd.Index.map
pd.Index.max
pd.DateTimeIndex.microsecond
pd.TimedeltaIndex.microseconds
pd.Index.min
pd.DateTimeIndex.minute
pd.DateTimeIndex.month
pd.Index.name
pd.Index.names
pd.DateTimeIndex.nanosecond
pd.TimedeltaIndex.nanoseconds
pd.Index.nbytes
pd.Index.ndim
pd.Index.nlevels
pd.Index.nunique
pd.Index.putmask
pd.DateTimeIndex.quarter
pd.RangeIndex
pd.Index.rename
pd.Index.repeat
pd.DateTimeIndex.second
pd.TimedeltaIndex.seconds
pd.Index.shape
pd.Index.size
pd.Index.sort_values
pd.Index.symmetric_difference
pd.Index.T
pd.Index.take
pd.TimedeltaIndex
pd.Index.to_frame
pd.Index.to_list
pd.Index.to_numpy
pd.Index.to_series
pd.Index.tolist
pd.UInt64Index
pd.Index.union
pd.Index.unique
pd.Index.values
pd.DateTimeIndex.week
pd.DateTimeIndex.weekday
pd.DateTimeIndex.weekofyear
pd.Index.where
pd.DateTimeIndex.year
TimeDelta
TimeDelta
pd.Timedelta.ceil
pd.Timedelta.components
pd.Timedelta.days
pd.Timedelta.delta
pd.Timedelta.floor
pd.Timedelta.microseconds
pd.Timedelta.nanoseconds
pd.Timedelta.round
pd.Timedelta.seconds
pd.Timedelta
pd.Timedelta.to_numpy
pd.Timedelta.to_pytimedelta
pd.Timedelta.to_timedelta64
pd.Timedelta.total_seconds
pd.Timedelta.value
Timestamp
Timestamp
pd.Timestamp.ceil
pd.Timestamp.date
pd.Timestamp.day
pd.Timestamp.day_name
pd.Timestamp.day_of_week
pd.Timestamp.day_of_year
pd.Timestamp.dayofweek
pd.Timestamp.dayofyear
pd.Timestamp.days_in_month
pd.Timestamp.daysinmonth
pd.Timestamp.floor
pd.Timestamp.hour
pd.Timestamp.is_leap_year
pd.Timestamp.is_month_end
pd.Timestamp.is_month_start
pd.Timestamp.is_quarter_end
pd.Timestamp.is_quarter_start
pd.Timestamp.is_year_end
pd.Timestamp.is_year_start
pd.Timestamp.isocalendar
pd.Timestamp.isoformat
pd.Timestamp.microsecond
pd.Timestamp.month
pd.Timestamp.month_name
pd.Timestamp.nanosecond
pd.Timestamp.normalize
pd.Timestamp.now
pd.Timestamp.quarter
pd.Timestamp.round
pd.Timestamp.second
pd.Timestamp.strftime
pd.Timestamp
pd.Timestamp.toordinal
pd.Timestamp.value
pd.Timestamp.week
pd.Timestamp.weekday
pd.Timestamp.weekofyear
pd.Timestamp.year
Numpy
User Defined Functions (UDFs)
Machine Learning
Machine Learning
Scikit Learn
Scikit Learn
sklearn.cluster
sklearn.ensemble
sklearn.feature_extraction
sklearn.linear_model
sklearn.metrics
sklearn.model_selection
sklearn.naive_bayes
sklearn.preprocessing
sklearn.svm
Miscellaneous Functions
Bodo Platform SDK Reference
Release Notes
Release Notes
Home
API Reference
BodoSQL Reference
API Reference
Aggregations and Window Functions
AVG
¶
AVG
Compute the mean of the the column/group/window. Supported on all numeric types.
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