I will make a stacked bar chart in matplotlib. Somehow it doesnt include all the bar chart that i gave him (there should be like 50 bar charts stacked on each other)
The code:
N=45 #numbers of columns
max_el=50
ind=np.arrange(N)
for bar in range(0,max_el):
y=[dic[value][bar] for value in dic]
plt.bar(ind,y,)
plt.show()
note: I used the similar code and same data and made a stacked bar chart with plotly (which worked)
With plotly
With matplotlib
Some of the values of variables are zeros or 0.1. Could that be the problem ?
As described in the comments, you need to add a bottoms array that keeps track of how much each should be moved up from the 0 line. Otherwise, they all start plotting a 0 and overplot one another, with the tallest one sticking up to its values and each one hiding those that were plotted before.
Related
I created a graph object bar chart that has two different y-axes so that I can chart two different of different units for each category. However, now I'd like to add two horizontal lines. They won't be using values from the same y-axis though.
fig = go.Figure(
data=[
go.Bar(name='Bar 1',
x=category_x,
y=measure_1,
yaxis='y',
offsetgroup=1),
go.Bar(name='Bar 2',
x=category_x,
y=measure_2,
yaxis='y2',
offsetgroup=2)
]
)
Things look fine up to here.
Now, I'd like to add one horizontal line based off values from the first y-axis and another horizontal line based off values from the second y-axis. I tried using fig.add_hline() for this, but then both horizontal lines are displayed using values from the first y-axis. What should I be doing instead?
Good evening all,
I have a pd.dataframe called plot_eigen_vecs_df which is of (3,11) dimension, and I am plotting each column value grouped by rows on a bar chart. I am using the following code:
plot_eigen_vecs_df.plot(kind='bar', figsize=(12, 8),
title='First 3 PCs factor loadings',
xlabel='Evects', legend=True)
The result is this graph:
enter image description here
I would like to keep the graph (grouped) exactly as it is, but I need to show the numeric value above each bars.
Thank you
I tried the add_label method, but unfortunately I am currently using a version of pyplot which is not the most recent, so .add_label doesn't work for me. Could you please help on the matter?
I'm working with TraMineR and I don't know how to arrange my plot. So basically what i would like to have the legend under the plot and to remove the space between the x and y axis. Any help is welcomed.
The plot:
Sample code:
seqdplot(Activities.seq, with.legend=FALSE)
legend("bottom", legend=attr(Activities.seq, "labels"),
fill=attr(Activities.seq, "cpal"),
inset=-.1, bty="o", xpd=NA, cex=.75,ncol=3)
The family of seqplot functions offers a series of arguments to control the legend as well as the axes. Look at the help page of seqplot (and of plot.stslist.statd for specific seqdplot parameters).
For instance, you can suppress the x-axis with axes=FALSE, and the y-axis with yaxis=FALSE.
To print the legend you can let seqdplot display it automatically using the default with.legend=TRUE option and control it with for examples cex.legend for the font size, ltext for the text. You can also use the ncol argument to set the number of columns in the legend.
The seqplot functions use by default layout to organize the graphic area between the plots and the legend. If you need more fine tuning (e.g. to change the default par(mar=c(5.1,4.1,4.1,2.1)) margins around the plot and the legend), you should create separately the plot(s) and the legend and then organize them yourself using e.g. layout or par(mfrow=...). In that case, the separate graphics should be created by setting with.legend=FALSE, which prevents the display of the legend and disables the automatic use of layout.
The color legend is easiest obtained with seqlegend.
I illustrate with the mvad data that ships with TraMineR. First the default plot with the legend. Note the use of border=NA to suppress the too many vertical black lines.
library(TraMineR)
data(mvad)
mvad.scode <- c("EM", "FE", "HE", "JL", "SC", "TR")
mvad.seq <- seqdef(mvad, 17:86,
states = mvad.scode,
xtstep = 6)
# Default plot with the legend,
seqdplot(mvad.seq, border=NA)
Now, we suppress the x and y axes and modify the display of the legend
seqdplot(mvad.seq, border=NA,
axes=FALSE, yaxis=FALSE, ylab="",
cex.legend=1.3, ncol=6, legend.prop=.11)
Here is how you can control the space between the plot and the x and y axes
seqdplot(mvad.seq, border=NA, yaxis=FALSE, xaxis=FALSE, with.legend=FALSE)
axis(2, line=-1)
axis(1, line=0)
Creating the legend separately and reducing the left, top, and right margins around the legend
op <- par(mar=c(5.1,0.1,0.1,0.1))
seqlegend(mvad.seq, ncol=2, cex=2)
par(op)
I am working with a semi-large data set of approx 100,000 records. When I plot a df column as a line with the code below the plot takes approx 2 seconds.
with plt.style.context('ggplot'):
plt.figure(3,figsize=(16,12))
plt.subplot(411)
df_pca_std['PC1_resid'].plot(title ="PC1 Residual", color='r')
#If I change the plot to a bar (no other change)
df_X_std['PC1_resid'].plot(**kind='bar'**, title ="PC1 Residual", color='r')
it takes 112 seconds and the render changes like this (jumbled x axis):
I have suppressed the axis and changed the style but neither helped. Anyone have ideas how to better render and take less time? The data being plotted is being checked for mean reversion and is better displayed as bar plot.
Not the best charts visually but at least it renders. Plotted 2.1 million bars in 14.2 secs.
import pygal
bar_chart = pygal.Bar()
bar_chart.add('PC1_residuals',df_X_std['PC1_resid'])
bar_chart.render_to_file('bar_chart.svg')
One possible solution: I do not actually need to plot bars but can use the very fast line plot and the 'fill_between' attribute to color the plot from zero to the line. The effect is similar to plotting all the bars in a fraction of the time.
Use pydatetime method of DatetimeIndex to convert Date (the df index) to an array of datetime.datetime's that can be used by matplotlib then change the plot.
plotDates = mpl.date2num(df.index.to_pydatetime())
plt.fill_between(plotDates,0,df_pca_std['PC1_resid'], alpha=0.5)
How can I create a scatter plot legend without two symbols showing up each time? I can understand why you'd want this when you're joining symbols by lines, but for a pure scatter plot, all I want in the legend is one example of the symbol. This plot from a previous stackoverflow post shows the kind of thing I mean:
In the legend command you can use the scatterpoints option:
ax.legend(loc=0, scatterpoints = 1)
For a normal plot, it is the option numpoints.
Here you can find more information about the keyword arguments for the legend: http://matplotlib.sourceforge.net/api/pyplot_api.html#matplotlib.pyplot.legend