eland.Series#
- class eland.Series(es_client: Optional[Elasticsearch] = None, es_index_pattern: Optional[str] = None, name: Optional[str] = None, es_index_field: Optional[str] = None, _query_compiler: Optional[QueryCompiler] = None)#
pandas.Series like API that proxies into Elasticsearch index(es).
Parameters#
- es_clientelasticsearch.Elasticsearch
A reference to a Elasticsearch python client
- es_index_patternstr
An Elasticsearch index pattern. This can contain wildcards.
- es_index_fieldstr
The field to base the series on
Notes#
If the Elasticsearch index is deleted or index mappings are changed after this object is created, the object is not rebuilt and so inconsistencies can occur.
See Also#
Examples#
>>> ed.Series(es_client='http://localhost:9200', es_index_pattern='flights', name='Carrier') 0 Kibana Airlines 1 Logstash Airways 2 Logstash Airways 3 Kibana Airlines 4 Kibana Airlines ... 13054 Logstash Airways 13055 Logstash Airways 13056 Logstash Airways 13057 JetBeats 13058 JetBeats Name: Carrier, Length: 13059, dtype: object
- __init__(es_client: Optional[Elasticsearch] = None, es_index_pattern: Optional[str] = None, name: Optional[str] = None, es_index_field: Optional[str] = None, _query_compiler: Optional[QueryCompiler] = None) None #
pandas.DataFrame/Series like API that proxies into Elasticsearch index(es).
Parameters#
- clientelasticsearch.Elasticsearch
A reference to a Elasticsearch python client
Methods
__init__
([es_client, es_index_pattern, ...])pandas.DataFrame/Series like API that proxies into Elasticsearch index(es).
add
(right)Return addition of series and right, element-wise (binary operator add).
describe
()Generate descriptive statistics that summarize the central tendency, dispersion and shape of a dataset’s distribution, excluding NaN values.
div
(right)Return floating division of series and right, element-wise (binary operator truediv).
divide
(right)Return floating division of series and right, element-wise (binary operator truediv).
es_info
()es_match
(text, *[, match_phrase, ...])Filters data with an Elasticsearch
match
ormatch_phrase
query depending on the given parameters.filter
([items, like, regex, axis])Subset the dataframe rows or columns according to the specified index labels.
floordiv
(right)Return integer division of series and right, element-wise (binary operator floordiv //).
head
([n])hist
([by, ax, grid, xlabelsize, xrot, ...])Draw histogram of the input series using matplotlib.
isin
(other)isna
()Detect missing values.
isnull
()Detect missing values.
mad
([numeric_only])Return median absolute deviation for a Series
max
([numeric_only])Return the maximum of the Series values
mean
([numeric_only])Return the mean of the Series values
median
([numeric_only])Return the median of the Series values
min
([numeric_only])Return the minimum of the Series values
mod
(right)Return modulo of series and right, element-wise (binary operator mod %).
mode
([es_size])Calculate mode of a series
mul
(right)Return multiplication of series and right, element-wise (binary operator mul).
multiply
(right)Return multiplication of series and right, element-wise (binary operator mul).
notna
()Detect existing (non-missing) values.
notnull
()Detect existing (non-missing) values.
nunique
()Return the number of unique values in a Series
pow
(right)Return exponential power of series and right, element-wise (binary operator pow).
quantile
([q])Used to calculate quantile for a given Series.
radd
(left)Return addition of series and left, element-wise (binary operator add).
rdiv
(left)Return division of series and left, element-wise (binary operator div).
rdivide
(left)Return division of series and left, element-wise (binary operator div).
rename
(new_name)Rename name of series.
rfloordiv
(left)Return integer division of series and left, element-wise (binary operator floordiv //).
rmod
(left)Return modulo of series and left, element-wise (binary operator mod %).
rmul
(left)Return multiplication of series and left, element-wise (binary operator mul).
rmultiply
(left)Return multiplication of series and left, element-wise (binary operator mul).
rpow
(left)Return exponential power of series and left, element-wise (binary operator pow).
rsub
(left)Return subtraction of series and left, element-wise (binary operator sub).
rsubtract
(left)Return subtraction of series and left, element-wise (binary operator sub).
rtruediv
(left)Return division of series and left, element-wise (binary operator div).
sample
([n, frac, random_state])std
([numeric_only])Return standard deviation for a Series
sub
(right)Return subtraction of series and right, element-wise (binary operator sub).
subtract
(right)Return subtraction of series and right, element-wise (binary operator sub).
sum
([numeric_only])Return the sum of the Series values
tail
([n])to_numpy
()Not implemented.
to_pandas
([show_progress])to_string
([buf, na_rep, float_format, ...])Render a string representation of the Series.
truediv
(right)Return floating division of series and right, element-wise (binary operator truediv).
unique
()Returns all unique values within a Series.
value_counts
([es_size])Return the value counts for the specified field.
var
([numeric_only])Return variance for a Series
Attributes
Return the dtype object of the underlying data.
Return the pandas dtypes in the DataFrame.
Determines if the Series is empty.
Return the Elasticsearch type of the underlying data.
Return the Elasticsearch dtypes in the index
es_field_name
Returns es_field_name: str Return the Elasticsearch field name for this series
Return eland index referencing Elasticsearch field to index a DataFrame/Series
Returns 1 by definition of a Series
Return a tuple representing the dimensionality of the Series.
Return an int representing the number of elements in this object.