Paguro
paguro.Collection.iter_slices
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bernardodionisi/paguro
Installation
Tutorials
API
Paguro
bernardodionisi/paguro
Installation
Installation
Getting Started
Tutorials
Tutorials
User Guide
API
API
Validation
Validation
p
vcol
p
vframe
p
vrelations
Dataset
Dataset
C
Dataset
Dataset
Constructors
Constructors
M
__
init__
Validation + Model
Validation + Model
Validation
Validation
M
with_
validation
P
validation
M
validate
Model
Model
P
vcol
P
model
M
with_
model
M
without_
model
M
collect_
model_
blueprint
Information
Information
M
with_
info
M
with_
name
EDA
EDA
M
skim
Export
Export
M
to_
polars
M
to_
dataframe
M
to_
lazyframe
Polars Methods
Polars Methods
Adapted
Adapted
M
write_
parquet
M
lazy
M
group_
by
M
group_
by_
dynamic
M
rolling
M
join
M
join_
asof
M
join_
where
M
merge_
sorted
M
vstack
M
rename
Delegated
Delegated
M
set_
sorted
M
approx_
n_
unique
M
bottom_
k
M
cast
M
clear
M
clone
M
collect_
schema
P
columns
M
corr
M
count
M
describe
M
drop
M
drop_
in_
place
M
drop_
nans
M
drop_
nulls
P
dtypes
M
equals
M
estimated_
size
M
explode
M
extend
M
fill_
nan
M
fill_
null
M
filter
P
flags
M
fold
M
gather_
every
M
get_
column
M
get_
column_
index
M
get_
columns
M
glimpse
M
hash_
rows
M
head
P
height
M
hstack
M
insert_
column
M
interpolate
M
is_
duplicated
M
is_
empty
M
is_
unique
M
item
M
iter_
columns
M
iter_
rows
M
iter_
slices
M
limit
M
map_
columns
M
map_
rows
M
match_
to_
schema
M
max
M
max_
horizontal
M
mean
M
mean_
horizontal
M
median
M
melt
M
min
M
min_
horizontal
M
n_
chunks
M
n_
unique
M
null_
count
M
partition_
by
M
pipe
M
pivot
P
plot
M
product
M
quantile
M
rechunk
M
remove
M
replace_
column
M
reverse
M
row
M
rows
M
rows_
by_
key
M
sample
P
schema
M
select
M
select_
seq
P
shape
M
shift
M
shrink_
to_
fit
M
slice
M
sort
M
sql
M
std
P
style
M
sum
M
sum_
horizontal
M
tail
M
top_
k
M
transpose
M
unique
M
unnest
M
unpivot
M
unstack
M
update
M
upsample
M
var
P
width
M
with_
columns
M
with_
columns_
seq
M
with_
row_
count
M
with_
row_
index
M
write_
avro
M
write_
clipboard
M
write_
csv
M
write_
database
M
write_
delta
M
write_
excel
M
write_
iceberg
M
write_
ipc
M
write_
ipc_
stream
M
write_
json
M
write_
ndjson
M
to_
arrow
M
to_
dict
M
to_
dicts
M
to_
dummies
M
to_
init_
repr
M
to_
jax
M
to_
numpy
M
to_
pandas
M
to_
series
M
to_
struct
M
to_
torch
C
Lazy
Dataset
Lazy
Dataset
Constructors
Constructors
M
__
init__
Validation + Model
Validation + Model
Validation
Validation
M
with_
validation
Model
Model
M
without_
model
Export
Export
M
to_
polars
Polars Methods
Polars Methods
Adapted
Adapted
M
sink_
parquet
M
collect
M
group_
by
M
group_
by_
dynamic
M
rolling
M
join
M
join_
asof
M
join_
where
M
merge_
sorted
M
rename
Delegated
Delegated
M
set_
sorted
M
lazy
M
approx_
n_
unique
M
bottom_
k
M
cache
M
cast
M
clear
M
clone
M
collect_
async
M
collect_
batches
M
collect_
schema
P
columns
M
count
M
describe
M
drop
M
drop_
nans
M
drop_
nulls
P
dtypes
M
explain
M
explode
M
fetch
M
fill_
nan
M
fill_
null
M
filter
M
first
M
gather_
every
M
head
M
inspect
M
interpolate
M
last
M
limit
M
map_
batches
M
match_
to_
schema
M
max
M
mean
M
median
M
melt
M
min
M
null_
count
M
pipe
M
pipe_
with_
schema
M
profile
M
quantile
M
remote
M
remove
M
reverse
P
schema
M
select
M
select_
seq
M
shift
M
show_
graph
M
sink_
batches
M
sink_
csv
M
sink_
ipc
M
sink_
ndjson
M
slice
M
sort
M
sql
M
std
M
sum
M
tail
M
top_
k
M
unique
M
unnest
M
unpivot
M
update
M
var
P
width
M
with_
columns
M
with_
columns_
seq
M
with_
context
M
with_
row_
count
M
with_
row_
index
Properties
Properties
P
vcol
P
model
Methods
Methods
M
with_
model
M
with_
info
M
with_
name
Collection
Collection
C
Collection
Collection
Constructors
Constructors
M
__
init__
Config
Config
M
set_
scope
M
set_
scope_
by_
index
Delegated
Delegated
M
set_
sorted
M
approx_
n_
unique
M
bottom_
k
M
cast
M
clear
M
clone
M
collect_
model_
blueprint
M
collect_
schema
M
corr
M
count
M
describe
M
drop
M
drop_
in_
place
M
drop_
nans
M
drop_
nulls
M
equals
M
estimated_
size
M
explode
M
extend
M
fill_
nan
M
fill_
null
M
filter
M
fold
M
gather_
every
M
get_
column
M
get_
column_
index
M
get_
columns
M
glimpse
M
hash_
rows
M
head
M
hstack
M
insert_
column
M
interpolate
M
is_
duplicated
M
is_
empty
M
is_
unique
M
item
M
iter_
columns
M
iter_
rows
M
iter_
slices
M
limit
M
map_
columns
M
map_
rows
M
match_
to_
schema
M
max
M
max_
horizontal
M
mean
M
mean_
horizontal
M
median
M
melt
M
merge_
sorted
M
min
M
min_
horizontal
M
n_
chunks
M
n_
unique
M
null_
count
M
partition_
by
M
pipe
M
pivot
M
product
M
quantile
M
rechunk
M
remove
M
rename
M
replace_
column
M
reverse
M
row
M
rows
M
rows_
by_
key
M
sample
M
select
M
select_
seq
M
shift
M
shrink_
to_
fit
M
skim
M
slice
M
sort
M
sql
M
std
M
sum
M
sum_
horizontal
M
tail
M
top_
k
M
transpose
M
unique
M
unnest
M
unpivot
M
unstack
M
update
M
upsample
M
var
M
vstack
M
with_
columns
M
with_
columns_
seq
M
with_
name
M
with_
row_
count
M
with_
row_
index
M
without_
model
M
to_
arrow
M
to_
dataframe
M
to_
dummies
M
to_
init_
repr
M
to_
jax
M
to_
lazyframe
M
to_
numpy
M
to_
pandas
M
to_
polars
M
to_
series
M
to_
struct
M
to_
torch
Methods
Methods
M
lazy
M
items
M
keys
M
values
M
concat
M
group_
by
M
join
Properties
Properties
P
columns
P
dtypes
P
flags
P
height
P
model
P
plot
P
schema
P
shape
P
style
P
vcol
P
width
Export
Export
M
to_
dict
C
Lazy
Collection
Lazy
Collection
Constructors
Constructors
M
__
init__
Delegated
Delegated
M
set_
sorted
M
collect
M
approx_
n_
unique
M
bottom_
k
M
cache
M
cast
M
clear
M
clone
M
collect_
async
M
collect_
batches
M
collect_
model_
blueprint
M
collect_
schema
M
count
M
describe
M
drop
M
drop_
nans
M
drop_
nulls
M
explain
M
explode
M
fetch
M
fill_
nan
M
fill_
null
M
filter
M
first
M
gather_
every
M
head
M
inspect
M
interpolate
M
last
M
limit
M
map_
batches
M
match_
to_
schema
M
max
M
mean
M
median
M
melt
M
merge_
sorted
M
min
M
null_
count
M
pipe
M
pipe_
with_
schema
M
profile
M
quantile
M
remote
M
remove
M
rename
M
reverse
M
select
M
select_
seq
M
shift
M
show_
graph
M
skim
M
slice
M
sort
M
sql
M
std
M
sum
M
tail
M
top_
k
M
unique
M
unnest
M
unpivot
M
update
M
var
M
with_
columns
M
with_
columns_
seq
M
with_
context
M
with_
name
M
with_
row_
count
M
with_
row_
index
M
without_
model
M
to_
dataframe
M
to_
lazyframe
M
to_
polars
Properties
Properties
P
columns
P
dtypes
P
model
P
schema
P
vcol
P
width
…
…
Validation
Validation
Base Models
Base Models
C
VFrame
Model
Validators
Validators
C
Valid
Column
Valid
Column
Settings
Settings
M
with_
name
Validation
Validation
M
validate
Methods
Methods
M
gather_
predicates
Information
Information
M
with_
info
Export
Export
M
serialize
M
to_
schema
C
Valid
Frame
Valid
Frame
Settings
Settings
M
with_
name
M
with_
columns_
policy
Information
Information
M
with_
info
Transformations
Transformations
M
transform
Validation
Validation
M
validate
Methods
Methods
M
gather_
predicates
C
Valid
Relations
Valid
Relations
Validation
Validation
M
validate
Exceptions
Exceptions
Validation
Error
Read/Scan
Read/Scan
Read
Read
F
read_
parquet
F
read_
ipc
F
read_
avro
F
read_
csv
F
read_
database_
uri
F
read_
delta
F
read_
json
F
read_
excel
F
read_
ndjson
F
read_
ods
Scan
Scan
F
scan_
parquet
F
scan_
ipc
F
scan_
csv
F
scan_
delta
F
scan_
ndjson
F
scan_
iceberg
F
scan_
pyarrow_
dataset
Utilities
Utilities
C
Config
Config
Constructors
Constructors
M
__
init__
Display
Display
M
set_
dataset_
ashi_
repr
Representation
Representation
M
set_
width_
chars
M
set_
styled
Validation
Validation
M
set_
auto_
validation_
mode
M
set_
auto_
validation_
limit
Settings
Settings
M
load
M
load_
from_
file
M
restore_
defaults
M
save
M
save_
to_
file
M
state
Special methods
Special methods
M
__
call__
F
show_
versions
Typing
Typing
V
Validation
Mode
V
Validator
Or
Expr
V
Into
Validators
V
Into
Validation
V
Fields
Validators
V
Into
Keep
Columns
V
On
Success
V
On
Failure
V
On
Failure
Extra
paguro.
Collection.
iter_slices
(
n_rows
:
int
=
10000
)
→
dict
[
str
,
Iterator
[
polars.DataFrame
]
]
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