maxframe.dataframe.DataFrame

class maxframe.dataframe.DataFrame(data=None, index=None, columns=None, dtype=None, copy=False, chunk_size=None, gpu=None, sparse=None, num_partitions=None)

__init__(data=None, index=None, columns=None, dtype=None, copy=False, chunk_size=None, gpu=None, sparse=None, num_partitions=None)

Methods

__init__([data, index, columns, dtype, ...])
abs()
add(other[, axis, level, fill_value])	Get Addition of dataframe and other, element-wise (binary operator add).
add_prefix(prefix)	Prefix labels with string prefix.
add_suffix(suffix)	Suffix labels with string suffix.
agg([func, axis])
aggregate([func, axis])
align(other[, join, axis, level, copy, ...])	Align two objects on their axes with the specified join method.
all([axis, bool_only, skipna, level, method])
any([axis, bool_only, skipna, level, method])
append(other[, ignore_index, ...])
apply(func[, axis, raw, result_type, args, ...])	Apply a function along an axis of the DataFrame.
assign(**kwargs)	Assign new columns to a DataFrame.
astype(dtype[, copy, errors])	Cast a pandas object to a specified dtype dtype.
backfill([axis, inplace, limit, downcast])	Synonym for DataFrame.fillna() with method='bfill'.
bfill([axis, inplace, limit, downcast])	Synonym for DataFrame.fillna() with method='bfill'.
copy()
copy_from(obj)
copy_to(target)
corr([method, min_periods])	Compute pairwise correlation of columns, excluding NA/null values.
corrwith(other[, axis, drop, method])	Compute pairwise correlation.
count([axis, level, numeric_only])
cummax([axis, skipna])
cummin([axis, skipna])
cumprod([axis, skipna])
cumsum([axis, skipna])
describe([percentiles, include, exclude])
diff([periods, axis])	First discrete difference of element.
div(other[, axis, level, fill_value])	Get Floating division of dataframe and other, element-wise (binary operator truediv).
drop([labels, axis, index, columns, level, ...])	Drop specified labels from rows or columns.
drop_duplicates([subset, keep, inplace, ...])	Return DataFrame with duplicate rows removed.
dropna([axis, how, thresh, subset, inplace])	Remove missing values.
duplicated([subset, keep, method])	Return boolean Series denoting duplicate rows.
eq(other[, axis, level, fill_value])	Get Equal to of dataframe and other, element-wise (binary operator eq).
eval(expr[, inplace])	Evaluate a string describing operations on DataFrame columns.
ewm([com, span, halflife, alpha, ...])	Provide exponential weighted functions.
execute([session])
expanding([min_periods, center, axis])	Provide expanding transformations.
explode(column[, ignore_index])	Transform each element of a list-like to a row, replicating index values.
ffill([axis, inplace, limit, downcast])	Synonym for DataFrame.fillna() with method='ffill'.
fillna([value, method, axis, inplace, ...])	Fill NA/NaN values using the specified method.
floordiv(other[, axis, level, fill_value])	Get Integer division of dataframe and other, element-wise (binary operator floordiv).
from_records(records, **kw)
from_tensor(in_tensor[, index, columns])
ge(other[, axis, level, fill_value])	Get Greater than or equal to of dataframe and other, element-wise (binary operator ge).
groupby([by, level, as_index, sort, group_keys])
gt(other[, axis, level, fill_value])	Get Greater than of dataframe and other, element-wise (binary operator gt).
head([n])	Return the first n rows.
insert(loc, column, value[, allow_duplicates])	Insert column into DataFrame at specified location.
isin(values)	Whether each element in the DataFrame is contained in values.
isna()	Detect missing values.
isnull()	Detect missing values.
iterrows([batch_size, session])	Iterate over DataFrame rows as (index, Series) pairs.
itertuples([index, name, batch_size, session])	Iterate over DataFrame rows as namedtuples.
join(other[, on, how, lsuffix, rsuffix, ...])	Join columns of another DataFrame.
keys()	Get the 'info axis' (see Indexing for more).
kurt([axis, skipna, level, numeric_only, ...])
kurtosis([axis, skipna, level, ...])
le(other[, axis, level, fill_value])	Get Less than or equal to of dataframe and other, element-wise (binary operator le).
lt(other[, axis, level, fill_value])	Get Less than of dataframe and other, element-wise (binary operator lt).
mask(cond[, other, inplace, axis, level, ...])	Replace values where the condition is True.
max([axis, skipna, level, numeric_only, method])
mean([axis, skipna, level, numeric_only, method])
median([axis, skipna, level, numeric_only, ...])
melt([id_vars, value_vars, var_name, ...])	Unpivot a DataFrame from wide to long format, optionally leaving identifiers set.
memory_usage([index, deep])	Return the memory usage of each column in bytes.
merge(right[, how, on, left_on, right_on, ...])	Merge DataFrame or named Series objects with a database-style join.
min([axis, skipna, level, numeric_only, method])
mod(other[, axis, level, fill_value])	Get Modulo of dataframe and other, element-wise (binary operator mod).
mul(other[, axis, level, fill_value])	Get Multiplication of dataframe and other, element-wise (binary operator mul).
multiply(other[, axis, level, fill_value])	Get Multiplication of dataframe and other, element-wise (binary operator mul).
ne(other[, axis, level, fill_value])	Get Not equal to of dataframe and other, element-wise (binary operator ne).
notna()	Detect existing (non-missing) values.
notnull()	Detect existing (non-missing) values.
nunique([axis, dropna])	Count distinct observations over requested axis.
pad([axis, inplace, limit, downcast])	Synonym for DataFrame.fillna() with method='ffill'.
pct_change([periods, fill_method, limit, freq])	Percentage change between the current and a prior element.
pivot_table([values, index, columns, ...])	Create a spreadsheet-style pivot table as a DataFrame.
pop(item)	Return item and drop from frame.
pow(other[, axis, level, fill_value])	Get Exponential power of dataframe and other, element-wise (binary operator pow).
prod([axis, skipna, level, min_count, ...])
product([axis, skipna, level, min_count, ...])
quantile([q, axis, numeric_only, interpolation])	Return values at the given quantile over requested axis.
query(expr[, inplace])	Query the columns of a DataFrame with a boolean expression.
radd(other[, axis, level, fill_value])	Get Addition of dataframe and other, element-wise (binary operator radd).
rdiv(other[, axis, level, fill_value])	Get Floating division of dataframe and other, element-wise (binary operator rtruediv).
reindex(*args, **kwargs)	Conform Series/DataFrame to new index with optional filling logic.
reindex_like(other[, method, copy, limit, ...])	Return an object with matching indices as other object.
rename([mapper, index, columns, axis, copy, ...])	Alter axes labels.
rename_axis([mapper, index, columns, axis, ...])	Set the name of the axis for the index or columns.
replace([to_replace, value, inplace, limit, ...])	Replace values given in to_replace with value.
reset_index([level, drop, inplace, ...])	Reset the index, or a level of it.
rfloordiv(other[, axis, level, fill_value])	Get Integer division of dataframe and other, element-wise (binary operator rfloordiv).
rmod(other[, axis, level, fill_value])	Get Modulo of dataframe and other, element-wise (binary operator rmod).
rmul(other[, axis, level, fill_value])	Get Multiplication of dataframe and other, element-wise (binary operator rmul).
rolling(window[, min_periods, center, ...])	Provide rolling window calculations.
round([decimals])	Round a DataFrame to a variable number of decimal places.
rpow(other[, axis, level, fill_value])	Get Exponential power of dataframe and other, element-wise (binary operator rpow).
rsub(other[, axis, level, fill_value])	Get Subtraction of dataframe and other, element-wise (binary operator rsubtract).
rtruediv(other[, axis, level, fill_value])	Get Floating division of dataframe and other, element-wise (binary operator rtruediv).
sample([n, frac, replace, weights, ...])	Return a random sample of items from an axis of object.
select_dtypes([include, exclude])	Return a subset of the DataFrame's columns based on the column dtypes.
sem([axis, skipna, level, ddof, ...])
set_axis(labels[, axis, inplace])	Assign desired index to given axis.
set_index(keys[, drop, append, inplace, ...])	Set the DataFrame index using existing columns.
shift([periods, freq, axis, fill_value])	Shift index by desired number of periods with an optional time freq.
skew([axis, skipna, level, numeric_only, ...])
sort_index([axis, level, ascending, ...])	Sort object by labels (along an axis).
sort_values(by[, axis, ascending, inplace, ...])	Sort by the values along either axis.
stack([level, dropna])	Stack the prescribed level(s) from columns to index.
std([axis, skipna, level, ddof, ...])
sub(other[, axis, level, fill_value])	Get Subtraction of dataframe and other, element-wise (binary operator subtract).
sum([axis, skipna, level, min_count, ...])
tail([n])	Return the last n rows.
tiles()
to_odps_table(table[, partition, ...])	Write DataFrame object into a MaxCompute (ODPS) table.
to_pandas([session])
to_tensor()
transform(func[, axis, dtypes, skip_infer])	Call func on self producing a DataFrame with transformed values.
transpose()	Transpose index and columns.
truediv(other[, axis, level, fill_value])	Get Floating division of dataframe and other, element-wise (binary operator truediv).
tshift([periods, freq, axis])	Shift the time index, using the index's frequency if available.
var([axis, skipna, level, ddof, ...])
where(cond[, other, inplace, axis, level, ...])	Replace values where the condition is False.

Attributes

T
at	Access a single value for a row/column label pair.
columns
data
dtypes	Return the dtypes in the DataFrame.
iat
iloc
index
loc
ndim	Return an int representing the number of axes / array dimensions.
shape
size
type_name
values