Danfo.js
  • Danfo.js Documentation
  • Getting Started
  • API reference
    • General Functions
      • danfo.tensorflow
      • danfo. convertFunctionTotransformer
      • danfo.streamCsvTransformer
      • danfo.streamJSON
      • danfo.streamCSV
      • danfo.Utils
      • danfo.Str
      • danfo.Dt
      • danfo.dateRange
      • danfo.OneHotEncoder
      • danfo.StandardScaler
      • danfo.MinMaxScaler
      • danfo.LabelEncoder
      • danfo.toDateTime
      • danfo.getDummies
      • danfo.concat
      • danfo.merge
    • Input/Output
      • danfo.readExcel
      • danfo.toExcel
      • danfo.readJSON
      • danfo.toJSON
      • danfo.readCSV
      • danfo.toCSV
    • Series
      • Creating a Series
      • Series.append
      • Series.cumSum
      • Series.cumMax
      • Series.cumProd
      • Series.cumMin
      • Series.str.split
      • Series.str.len
      • Series.str.join
      • Series.str.trim
      • Series.str.substring
      • Series.str.substr
      • Series.str.slice
      • Series.str.search
      • Series.str.repeat
      • Series.str.replace
      • Series.str.lastIndexOf
      • Series.str.indexOf
      • Series.str.includes
      • Series.str.endsWith
      • Series.str.startsWith
      • Series.str.concat
      • Series.str.charAt
      • Series.str.toUpperCase
      • Series.str.toLowerCase
      • Series.str.capitalize
      • Series.dt.seconds
      • Series.dt.minutes
      • Series.dt.dayOfMonth
      • Series.dt.monthName
      • Series.dt.hours
      • Series.dt.dayOfWeek
      • Series.dt.dayOfWeek
      • Series.dt.month
      • Series.dt.year
      • Series.argMax
      • Series.argMin
      • Series.argSort
      • Series.replace
      • Series.isNa
      • Series.fillNa
      • Series.dropNa
      • Series.dropDuplicates
      • Series.valueCounts
      • Series.nUnique
      • Series.unique
      • Series.abs
      • Series.ne
      • Series.eq
      • Series.ge
      • Series.le
      • Series.gt
      • Series.lt
      • Series.iloc
      • Series.loc
      • Series.at
      • Series.iat
      • Series.ndim
      • Series.shape
      • Series.dtype
      • Series.values
      • Series.tensor
      • Series.index
      • Series.apply
      • Series.map
      • Series.setIndex
      • Series.resetIndex
      • Series.describe
      • Series.copy
      • Series.sortValues
      • Series.var
      • Series.std
      • Series.round
      • Series.minimum
      • Series.maximum
      • Series.count
      • Series.sum
      • Series.max
      • Series.min
      • Series.mode
      • Series.median
      • Series.mean
      • Series.mod
      • Series.pow
      • Series.div
      • Series.mul
      • Series.sub
      • Series.add
      • Series.sample
      • Series.tail
      • Series.head
      • Series.and
      • Series.or
    • Dataframe
      • Creating a DataFrame
      • DataFrame.sortIndex
      • DataFrame.append
      • DataFrame.nUnique
      • DataFrame.tensor
      • DataFrame.print
      • DataFrame.toCSV
      • DataFrame.toJSON
      • DataFrame.toExcel
      • DataFrame.sortValues
      • DataFrame.setIndex
      • DataFrame.resetIndex
      • DataFrame.rename
      • DataFrame.drop
      • DataFrame.asType
      • DataFrame.shape
      • DataFrame.axis
      • DataFrame.ndim
      • DataFrame.values
      • DataFrame.selectDtypes
      • DataFrame.ctypes
      • DataFrame.index
      • DataFrame.loc
      • DataFrame.iloc
      • DataFrame.at
      • DataFrame.iat
      • DataFrame.head
      • DataFrame.tail
      • DataFrame.sample
      • DataFrame.add
      • DataFrame.sub
      • DataFrame.mul
      • DataFrame.div
      • DataFrame.pow
      • DataFrame.mod
      • DataFrame.mean
      • DataFrame.median
      • DataFrame.min
      • DataFrame.max
      • DataFrame.std
      • DataFrame.var
      • DataFrame.count
      • DataFrame.round
      • DataFrame.cumSum
      • DataFrame.cumMin
      • DataFrame.cumMax
      • DataFrame.cumProd
      • DataFrame.copy
      • DataFrame.describe
      • DataFrame.sum
      • DataFrame.abs
      • DataFrame.query
      • DataFrame.addColumn
      • DataFrame.groupby
      • DataFrame.column
      • DataFrame.fillNa
      • DataFrame.isNa
      • DataFrame.dropNa
      • DataFrame.apply
      • DataFrame.applyMap
      • DataFrame.It
      • DataFrame.gt
      • DataFrame.le
      • DataFrame.ge
      • DataFrame.ne
      • DataFrame.eq
      • DataFrame.replace
    • Configuration Options
    • Plotting
      • Timeseries Plots
      • Violin Plots
      • Box Plots
      • Tables
      • Pie Charts
      • Histograms
      • Scatter Plots
      • Bar Charts
      • Line Charts
      • Customizing your plots
    • Groupby
      • Groupby.getGroups
      • Groupby.col
      • Groupby.max
      • Groupby.min
      • Groupby.sum
      • Groupby.mean
      • Groupby.std
      • Groupby.var
      • Groupby.count
      • Groupby.cumSum
      • Groupby.cumMax
      • Groupby.cumMin
      • Groupby.cumProd
      • Groupby.agg
  • User Guides
    • Migrating to the stable version of Danfo.js
    • Using Danfojs in React
    • Titanic Survival Prediction using Danfo.js and Tensorflow.js
  • Building Data Driven Applications with Danfo.js - Book
  • Contributing Guide
  • Release Notes
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On this page
  • Examples
  • Indexing specific rows by index
  • Index by a slice of row
  • Slice Series by boolean condition

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  1. API reference
  2. Series

Series.iloc

danfo.Series.iloc()

Parameters
Type
Description
Default

rows

Array or String slice

Array, string slice, index of row positions boolean mask to filter by.

Examples

.iloc() is primarily integer position based (from 0 to length-1 of the axis).

Allowed inputs are:

  • An integer, e.g. 5.

  • A list or array of integers, e.g. [4, 3, 0].

  • A boolean mask. E.g [ true, false, false ]

  • A string slice object with ints, e.g. "1:7"

Note: only **** the start label is included, and the end label is ignored.

.iloc will raiseIndexError if a requested indexer is out-of-bounds.

Indexing specific rows by index

const dfd = require("danfojs-node")

let s = new dfd.Series([12, 34, 2.2, 2, 30, 30, 2.1, 7])
s.iloc([0,5]).print()
╔═══╤════╗
║ 0 │ 12 ║
╟───┼────╢
║ 5 │ 30 ║
╚═══╧════╝

Index by a slice of row

const dfd = require("danfojs-node")

let s = new dfd.Series([12, 34, 2.2, 2, 30, 30, 2.1, 7])
s.iloc(["0:5"]).print()
╔═══╤═════╗
║ 0 │ 12  ║
╟───┼─────╢
║ 1 │ 34  ║
╟───┼─────╢
║ 2 │ 2.2 ║
╟───┼─────╢
║ 3 │ 2   ║
╟───┼─────╢
║ 4 │ 30  ║
╚═══╧═════╝

By specifying a start index in a slice, all values after that index are returned.

const dfd = require("danfojs-node")

let s = new dfd.Series([12, 34, 2.2, 2, 30, 30, 2.1, 7])
s.iloc(["5:"]).print()
╔═══╤═════╗
║ 5 │ 30  ║
╟───┼─────╢
║ 6 │ 2.1 ║
╟───┼─────╢
║ 7 │ 7   ║
╚═══╧═════╝

Slice Series by boolean condition

const dfd = require("danfojs-node")

let s = new dfd.Series([12, 34, 2.2, 2, 30, 30, 2.1, 7])
s.iloc(s.gt(20)).print()
╔═══╤════╗
║ 1 │ 34 ║
╟───┼────╢
║ 4 │ 30 ║
╟───┼────╢
║ 5 │ 30 ║
╚═══╧════╝
PreviousSeries.ltNextSeries.loc

Last updated 3 years ago

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The function also accepts string slices of the form [start: end], e.g "[0: 5]". This will return all values from index positions 0 to 4.

iloc