FloatColumn

class getml.data.columns.FloatColumn(name='', role='numerical', num=0, df_name='')

Handler for numerical data in the engine.

This is a handler for all numerical data in the getML engine, including time stamps.

Args:

name (str, optional): Name of the categorical column. role (str, optional): Role that the column plays. num (int, optional): Number of the column. df_name (str, optional):

name instance variable of the DataFrame containing this column.

Examples:

import numpy as np

import getml.data as data
import getml.engine as engine
import getml.data.roles as roles

# ----------------

engine.set_project("examples")

# ----------------
# Create a data frame from a JSON string

json_str = """{
    "names": ["patrick", "alex", "phil", "ulrike"],
    "column_01": [2.4, 3.0, 1.2, 1.4],
    "join_key": ["0", "1", "2", "3"],
    "time_stamp": ["2019-01-01", "2019-01-02", "2019-01-03", "2019-01-04"]
}"""

my_df = data.DataFrame(
    "MY DF",
    roles={
        "unused_string": ["names", "join_key", "time_stamp"],
        "unused_float": ["column_01"]}
).read_json(
    json_str
)

# ----------------

col1 = my_df["column_01"]

# ----------------

col2 = 2.0 - col1

my_df.add(col2, "name", roles.numerical)

# ----------------
# If you do not explicitly set a role,
# the assigned role will either be
# roles.unused_float.

col3 = (col1 + 2.0*col2) / 3.0

my_df["column_03"] = col3
my_df.set_role("column_03", roles.numerical)

Methods

abs()	Compute absolute value.
acos()	Compute arc cosine.
alias(alias)	Adds an alias to the column.
as_str()	Transforms column to a string.
asin()	Compute arc sine.
assert_equal([alias])	ASSERT EQUAL aggregation.
atan()	Compute arc tangent.
avg([alias])	AVG aggregation.
cbrt()	Compute cube root.
ceil()	Round up value.
cos()	Compute cosine.
count([alias])	COUNT aggregation.
day()	Extract day (of the month) from a time stamp.
erf()	Compute error function.
exp()	Compute exponential function.
floor()	Round down value.
gamma()	Compute gamma function.
hour()	Extract hour (of the day) from a time stamp.
is_inf()	Determine whether the value is infinite.
is_nan()	Determine whether the value is nan.
is_null()	Determine whether the value is nan.
lgamma()	Compute log-gamma function.
log()	Compute natural logarithm.
max([alias])	MAX aggregation.
median([alias])	MEDIAN aggregation.
min([alias])	MIN aggregation.
minute()	Extract minute (of the hour) from a time stamp.
month()	Extract month from a time stamp.
round()	Round to nearest.
second()	Extract second (of the minute) from a time stamp.
sin()	Compute sine.
sqrt()	Compute square root.
stddev([alias])	STDDEV aggregation.
sum([alias])	SUM aggregation.
tan()	Compute tangent.
to_numpy([sock])	Transform column to numpy array
update(condition, values)	Returns an updated version of this column.
var([alias])	VAR aggregation.
weekday()	Extract day of the week from a time stamp, Sunday being 0.
year()	Extract year from a time stamp.
yearday()	Extract day of the year from a time stamp.

Attributes

length	The length of the column (number of rows in the data frame).
monitor_url
name	The role of this column.
role	The role of this column.
unit	The unit of this column.