Plotly is a Python library which is used to design graphs, especially interactive graphs. It can plot various graphs and charts like histogram, barplot, boxplot, spreadplot and many more. It is mainly used in data analysis as well as financial analysis. plotly is an interactive visualization library.
Histogram using graph_objects class
Plotly provides the more generic go.Histogram class from plotly.graph_objects. But let us first understand what are histograms. Histogram have few important parts, which is described below:
- The title: The title play a role to describes the information admitted in the histogram.
- X-axis: The X-axis are intervals that show the scale of values which measures all fall under.
- Y-axis: The Y-axis shows the number of times that the values occurred within the intervals set by the X-axis.
- The bars: The height of the bar shows the number of times that the values occurred within the interval, while the width of the bar shows the interval that is covered. For a histogram with equal bins, the width should be the same across all bars.
Syntax: class plotly.graph_objects.Histogram(arg=None, alignmentgroup=None, autobinx=None, autobiny=None, bingroup=None, cumulative=None, customdata=None, customdatasrc=None, error_x=None, error_y=None, histfunc=None, histnorm=None, hoverinfo=None, hoverinfosrc=None, hoverlabel=None, hovertemplate=None, hovertemplatesrc=None, hovertext=None, hovertextsrc=None, ids=None, idssrc=None, legendgroup=None, marker=None, meta=None, metasrc=None, name=None, nbinsx=None, nbinsy=None, offsetgroup=None, opacity=None, orientation=None, selected=None, selectedpoints=None, showlegend=None, stream=None, text=None, textsrc=None, uid=None, uirevision=None, unselected=None, visible=None, x=None, xaxis=None, xbins=None, xcalendar=None, xsrc=None, y=None, yaxis=None, ybins=None, ycalendar=None, ysrc=None, **kwargs)
Parameters:
| Name | Description |
|---|---|
| arg | dict of properties compatible with this constructor or an instance of plotly.graph_objects.Histogram |
| alignmentgroup | Set several traces linked to the same position axis or matching axes to the same alignmentgroup. This controls whether bars compute their positional range dependently or independently. |
| autobinx | Obsolete: since v1.42 each bin attribute is auto- determined separately and autobinx is not needed. However, we accept autobinx: true or false and will update xbins accordingly before deleting autobinx from the trace. |
| autobiny | Obsolete: since v1.42 each bin attribute is auto- determined separately and autobiny is not needed. However, we accept autobiny: true or false and will update ybins accordingly before deleting autobiny from the trace. |
| bingroup | Set a group of histogram traces which will have compatible bin settings. Note that traces on the same subplot and with the same “orientation” under barmode “stack”, “relative” and “group” are forced into the same bingroup, Using bingroup, traces under barmode “overlay” and on different axes (of the same axis type) can have compatible bin settings. Note that histogram and histogram2d* trace can share the same bingroup |
| cumulative | plotly.graph_objects.histogram.Cumulative instance or dict with compatible properties |
| customdata | Assigns extra data each datum. This may be useful when listening to hover, click and selection events. Note that, “scatter” traces also appends customdata items in the markers DOM elements |
| customdatasrc | Sets the source reference on Chart Studio Cloud for customdata . |
| error_x | plotly.graph_objects.histogram.ErrorX instance or dict with compatible properties |
| error_y | plotly.graph_objects.histogram.ErrorY instance or dict with compatible properties |
| histfunc | Specifies the binning function used for this histogram trace. If “count”, the histogram values are computed by counting the number of values lying inside each bin. If “sum”, “avg”, “min”, “max”, the histogram values are computed using the sum, the average, the minimum or the maximum of the values lying inside each bin respectively. |
| histnorm | Specifies the type of normalization used for this histogram trace. If “”, the span of each bar corresponds to the number of occurrences (i.e. the number of data points lying inside the bins). If “percent” / “probability”, the span of each bar corresponds to the percentage / fraction of occurrences with respect to the total number of sample points (here, the sum of all bin HEIGHTS equals 100% / 1). If “density”, the span of each bar corresponds to the number of occurrences in a bin divided by the size of the bin interval (here, the sum of all bin AREAS equals the total number of sample points). If probability density, the area of each bar corresponds to the probability that an event will fall into the corresponding bin (here, the sum of all bin AREAS equals 1). |
| hoverinfo | Determines which trace information appear on hover. If none or skip are set, no information is displayed upon hovering. But, if none is set, click and hover events are still fired. |
| hoverinfosrc | Sets the source reference on Chart Studio Cloud for hoverinfo . |
| hoverlabel | plotly.graph_objects.histogram.Hoverlabel instance or dict with compatible properties |
| hovertemplate | Template string used for rendering the information that appear on hover box. Note that this will override hoverinfo. Variables are inserted using %{variable}, for example “y: %{y}”. Numbers are formatted using d3-format’s syntax %{variable:d3-format}, for example “Price: %{y:$.2f}”. https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format for details on the formatting syntax. Dates are formatted using d3-time-format’s syntax %{variable|d3-time- format}, for example “Day: %{2019-01-01|%A}”. https://github.com/d3/d3-3.x-api- reference/blob/master/Time-Formatting.md#format for details on the date formatting syntax.Additionally, every attributes that can be specified per-point (the ones that are arrayOk: true) are available. variable binNumber Anything contained in tag <extra> is displayed in the secondary box, for example “<extra>{fullData.name}</extra>”. To hide the secondary box completely, use an empty tag <extra></extra>. |
| hovertemplatesrc | Sets the source reference on Chart Studio Cloud for hovertemplate |
| hovertext | same as text |
| hovertextsrc | Sets the source reference on Chart Studio Cloud for hovertext . |
| ids | Assigns id labels to each datum. These ids for object constancy of data points during animation. Should be an array of strings, not numbers or any other type. |
| idssrc | Sets the source reference on Chart Studio Cloud for ids . |
| legendgroup | Sets the legend group for this trace. Traces part of the same legend group hide/show at the same time when toggling legend items. |
| marker | plotly.graph_objects.histogram.Marker instance or dict with compatible properties |
| meta | Assigns extra meta information associated with this trace that can be used in various text attributes. Attributes such as trace name, graph, axis and colorbar title.text, annotation text rangeselector, updatemenues and sliders label text all support meta. To access the trace meta values in an attribute in the same trace, simply use %{meta[i]} where i is the index or key of the meta item in question. To access trace meta in layout attributes, use %{data[n[.meta[i]} where i is the index or key of the meta and n is the trace index. |
| metasrc | Sets the source reference on Chart Studio Cloud for meta . |
| name | Sets the trace name. The trace name appear as the legend item and on hover |
| nbinsx | Specifies the maximum number of desired bins. This value will be used in an algorithm that will decide the optimal bin size such that the histogram best visualizes the distribution of the data. Ignored if xbins.size is provided. |
| nbinsy | Specifies the maximum number of desired bins. This value will be used in an algorithm that will decide the optimal bin size such that the histogram best visualizes the distribution of the data. Ignored if ybins.size is provided. |
| offsetgroup | Set several traces linked to the same position axis or matching axes to the same offsetgroup where bars of the same position coordinate will line up. |
| opacity | Sets the opacity of the trace. |
| orientation | Sets the orientation of the bars. With “v” (“h”), the value of the each bar spans along the vertical (horizontal). |
| selected | plotly.graph_objects.histogram.Selected instance or dict with compatible properties |
| selectedpoints | Array containing integer indices of selected points. Has an effect only for traces that support selections. Note that an empty array means an empty selection where the unselected are turned on for all points, whereas, any other non-array values means no selection all where the selected and unselected styles have no effect. |
| showlegend | Determines whether or not an item corresponding to this trace is shown in the legend. |
| stream | plotly.graph_objects.histogram.Stream instance or dict with compatible properties |
| text | Sets hover text elements associated with each bar. If a single string, the same string appears over all bars. If an array of string, the items are mapped in order to the this trace’s coordinates. |
| textsrc | Sets the source reference on Chart Studio Cloud for text . |
| uid | Assign an id to this trace, Use this to provide object constancy between traces during animations and transitions. |
| uirevision | Controls persistence of some user-driven changes to the trace: constraintrange in parcoords traces, as well as some editable: true modifications such as name and colorbar.title. Defaults to layout.uirevision. Note that other user-driven trace attribute changes are controlled by layout attributes: trace.visible is controlled by layout.legend.uirevision, selectedpoints is controlled by layout.selectionrevision, and colorbar.(x|y) (accessible with config: {editable: true}) is controlled by layout.editrevision. Trace changes are tracked by uid, which only falls back on trace index if no uid is provided. So if your app can add/remove traces before the end of the data array, such that the same trace has a different index, you can still preserve user-driven changes if you give each trace a uid that stays with it as it moves. |
| unselected | plotly.graph_objects.histogram.Unselected instance or dict with compatible properties |
| visible | Determines whether or not this trace is visible. If “legendonly”, the trace is not drawn, but can appear as a legend item (provided that the legend itself is visible). |
| x | Sets the sample data to be binned on the x axis. |
| xaxis | Sets a reference between this trace’s x coordinates and a 2D cartesian x axis. If “x” (the default value), the x coordinates refer to layout.xaxis. If “x2”, the x coordinates refer to layout.xaxis2, and so on. |
| xbins | plotly.graph_objects.histogram.XBins instance or dict with compatible properties |
| xcalender | Sets the calendar system to use with x date data. |
| xsrc | Sets the source reference on Chart Studio Cloud for x |
| y | Sets the sample data to be binned on the y axis. |
| yaxis | Sets a reference between this trace’s y coordinates and a 2D cartesian y axis. If “y” (the default value), the y coordinates refer to layout.yaxis. If “y2”, the y coordinates refer to layout.yaxis2, and so on. |
| ybins | plotly.graph_objects.histogram.YBins instance or dict with compatible properties |
| ycalender | Sets the calendar system to use with y date data. |
| ysrc | Sets the source reference on Chart Studio Cloud for y . |
Example:
Python3
import plotly.express as pximport plotly.graph_objects as godf = px.data.iris()fig = go.Figure(data=[go.Histogram(x=df['sepal_width'])])fig.show() |
Output:
Horizontal Histogram
Horizontal histogram is a histogram in which the data is shown horizontally in the bars in graph. The data are grouped into categories or bins according to their values and range of bins.Y argument should be used instead of x argument to make horizontal histogram.
Example:
Python3
import plotly.express as pximport plotly.graph_objects as godf = px.data.iris()fig = go.Figure(data=[go.Histogram(y=df['sepal_width'])])fig.show() |
Output:
Stacked Histograms
Stacked histogram is a type of graph or graphical representation in which the data is represented in single bar with each different color. The bar can be either horizontal or vertical depend on the component.
Example:
Python3
import plotly.express as pximport plotly.graph_objects as godf = px.data.iris()fig = go.Figure()fig.add_trace(go.Histogram(x=df['sepal_width']))fig.add_trace(go.Histogram(x=df['species_id']))fig.update_layout(barmode='stack')fig.show() |
Output:
