Using the single chart example, I have a label for each piece of cake.
If I try to transform it in a faceted chart using this code
df=pd.read_csv("input.csv",keep_default_na=False)
base=alt.Chart(df).encode(
theta=alt.Theta(field="v", type="quantitative"),
color=alt.Color(field="k", type="nominal")
)
pie = base.mark_arc(outerRadius=100)
text = base.mark_text(radius=115,fill= "black").encode(alt.Text(field="v", type="quantitative", format=",.1f"))
alt.layer(pie, text, data=df).facet(column='label')
all the labels are all in the same wedge and then illegible (here the vega lite version vega lite version).
how to have a result similar to that of the single chart?
Thank you
f,n,k,v,label
1,3,0-5 %,99.7289972899729,Forest
1,4,5-10 %,0.27100271002710025,Forest
0,1,0-5 %,100.0,Non-Forest
254,5,0-5 %,99.0077177508269,unclassifiable
254,6,5-10 %,0.9922822491730982,unclassifiable
I must add:
stack=True as channel encoding option in the theta channel encoding;
and .resolve_scale( theta="independent" ) to the chart.
And it works (I learned this thanks to Mattijn van Hoek).
df=pd.read_csv("input.csv",keep_default_na=False)
base=alt.Chart(df).encode(
theta=alt.Theta(field="v", type="quantitative", stack=True),
color=alt.Color(field="k", type="nominal")
)
pie = base.mark_arc(outerRadius=100)
text = base.mark_text(radius=115,fill= "black").encode(alt.Text(field="v", type="quantitative", format=",.1f"))
alt.layer(pie, text, data=df).facet(column='label').resolve_scale(theta="independent")
I have a barplot in latex in tikz, that I want to scale (reduce width, increase length), but without the text having the same effect.
\begin{figure}
\centering
\resizebox{0.8\textwidth}{1.3\textwidth}{
\begin{tikzpicture}
\pgfplotsset{every tick label/.append style={font=\tiny}}
\begin{axis}[ xmajorgrids=true,
xbar, xmin=0,
xlabel={Gini Coefficient, OECD Countries \%},
symbolic y coords={{Australia},{Austria},{Belgium},{Canada},{Chile},{Costa Rica},{Czech Republic},{Denmark},{Estonia},{Finland},{France},{Germany},{Greece},{Hungary},{Iceland},{Ireland},{Israel},{Italy},{Japan},{Korea},{Latvia},{Lithuania},{Luxembourg},{Mexico},{Netherlands},{New Zealand},{Norway},{Poland},{Portugal},{Slovak Republic},{Slovenia},{South Africa},{Spain},{Sweden},{Switzerland},{Turkey},{United Kingdom},{United States}},
ytick=data,
nodes near coords, nodes near coords align={horizontal},
ytick=data,
]
\addplot[fill=blue!90,draw=black!70,tickwidth = 0pt,bar width=4pt,label style={font=\small}, tick label style={font=\small}] coordinates {(0.33,{Australia}) (0.284,{Austria}) (0.266,{Belgium}) (0.307,{Canada}) (0.454,{Chile}) (0.48,{Costa Rica}) (0.253,{Czech Republic}) (0.263,{Denmark}) (0.314,{Estonia}) (0.266,{Finland}) (0.291,{France}) (0.294,{Germany}) (0.333,{Greece}) (0.288,{Hungary}) (0.255,{Iceland}) (0.297,{Ireland}) (0.344,{Israel}) (0.328,{Italy}) (0.339,{Japan}) (0.355,{Korea}) (0.346,{Latvia}) (0.378,{Lithuania}) (0.304,{Luxembourg}) (0.458,{Mexico}) (0.285,{Netherlands}) (0.349,{New Zealand}) (0.262,{Norway}) (0.284,{Poland}) (0.331,{Portugal}) (0.241,{Slovak Republic}) (0.244,{Slovenia}) (0.62,{South Africa}) (0.341,{Spain}) (0.282,{Sweden}) (0.296,{Switzerland}) (0.404,{Turkey}) (0.351,{United Kingdom}) (0.391,{United States})};
\end{axis}
\end{tikzpicture}
}
\caption{\small{Gini coefficient, OECD countries, 2017 or latest available, source: \url{https://data.oecd.org/inequality/income-inequality.htm}}}
\label{fig:giniOECD}
\end{figure}
I would like the bar charts a bit further apart to each other, the blank areas on top and at the end to be removed, the markers (text within the chart that show the values) to be smaller and all the text to be at normal scale, not skewed like that.
Never ever use \resizebox (or \scalebox) for things that contain text.
to set the height and the width of a pgfplot, the height and width keywords can be used
don't put formatting instructions in arguments of macros like \caption. If you want the caption in another font size, you can adjust it with the help of the caption package
\documentclass{article}
\usepackage{pgfplots}
\usepackage{hyperref}
\usepackage[font=small]{caption}
\begin{document}
\begin{figure}[htbp]
\centering
\begin{tikzpicture}
\pgfplotsset{%
width=.8\textwidth,
height=1.5\textwidth
}
\begin{axis}[
xmajorgrids=true,
xbar,
xmin=0,
xlabel={Gini Coefficient, OECD Countries \%},
symbolic y coords={{Australia}, {Austria}, {Belgium}, {Canada}, {Chile}, {Costa Rica}, {Czech Republic}, {Denmark}, {Estonia}, {Finland}, {France}, {Germany}, {Greece}, {Hungary}, {Iceland}, {Ireland}, {Israel}, {Italy}, {Japan}, {Korea}, {Latvia}, {Lithuania}, {Luxembourg}, {Mexico}, {Netherlands}, {New Zealand}, {Norway}, {Poland}, {Portugal}, {Slovak Republic}, {Slovenia}, {South Africa}, {Spain}, {Sweden}, {Switzerland}, {Turkey}, {United Kingdom}, {United States}},
ytick=data,
nodes near coords,
nodes near coords align={horizontal},
enlarge y limits=0.02,
]
\addplot[fill=blue!90,draw=black!70,tickwidth = 0pt,bar width=4pt,label style={font=\small}, tick label style={font=\small}] coordinates {(0.33,{Australia}) (0.284,{Austria}) (0.266,{Belgium}) (0.307,{Canada}) (0.454,{Chile}) (0.48,{Costa Rica}) (0.253,{Czech Republic}) (0.263,{Denmark}) (0.314,{Estonia}) (0.266,{Finland}) (0.291,{France}) (0.294,{Germany}) (0.333,{Greece}) (0.288,{Hungary}) (0.255,{Iceland}) (0.297,{Ireland}) (0.344,{Israel}) (0.328,{Italy}) (0.339,{Japan}) (0.355,{Korea}) (0.346,{Latvia}) (0.378,{Lithuania}) (0.304,{Luxembourg}) (0.458,{Mexico}) (0.285,{Netherlands}) (0.349,{New Zealand}) (0.262,{Norway}) (0.284,{Poland}) (0.331,{Portugal}) (0.241,{Slovak Republic}) (0.244,{Slovenia}) (0.62,{South Africa}) (0.341,{Spain}) (0.282,{Sweden}) (0.296,{Switzerland}) (0.404,{Turkey}) (0.351,{United Kingdom}) (0.391,{United States})};
\end{axis}
\end{tikzpicture}
\caption{Gini coefficient, OECD countries, 2017 or latest available, source: \url{https://data.oecd.org/inequality/income-inequality.htm}}
\label{fig:giniOECD}
\end{figure}
\end{document}
I have series of monthly inventory data since 2017.
I have a series of inventory_forecasts since Dec2018
I am trying to plot the inventory data on a monthly-seasonal basis, and then overlay the inventory_forecasts of Jan2019 through Dec2019.
The dataframe looks like:
The first way I tried to make the chart does show all the data I want, but I'm unable to control the color of the inventory_zj line. Its color seems to be dominated by the color=year(date):N of the alt.Chart I configured. It is ignoring the color='green' I pass to the mark_line()
base = alt.Chart(inv.loc['2000':].reset_index(), title=f"usa total inventory").mark_line().encode(
x='month',
y="inventory",
color="year(date):N"
)
#this ignores my 'green' color instruction, and marks it the same light blue 2019 color
joe = base.mark_line(color='green').encode(
alt.Y('inventory_zj', scale=alt.Scale(zero=False), )
)
base+joe
I tried to use a layering system, but it's not working at all -- I cannot get it to display the "joe" layer
base = alt.Chart(inv.loc['2000':].reset_index(), title=f"usa total inventory").encode(
x='month(date)'
)
doe = base.mark_line().encode(
alt.Y('inventory', scale=alt.Scale(zero=False), ),
color="year(date):N"
)
joe = base.mark_line(color="green").encode(
alt.Y('inventory_zj', scale=alt.Scale(zero=False), ),
)
#looks identical to the first example
alt.layer(
doe, joe
).resolve_scale(
y='shared'
).configure_axisLeft(labelColor='black').configure_axisRight(labelColor='green',titleColor='green')
#independent shows a second y-axis (which is different from the left y-axis) but no line
alt.layer(
doe, joe
).resolve_scale(
y='independent'
).configure_axisLeft(labelColor='black').configure_axisRight(labelColor='green',titleColor='green')
I feel like i must be trying to assemble this chart in a fundamentally wrong way. I should be able to share teh same left y-axis, have the historic data colored by its year, and have a unique color for the 2019-forecasted data. But I seem to be making a mess of it.
As mentioned in the Customizing Visualizations docs, there are multiple ways to specify things like line color, with a well-defined hierarchy: encodings override mark properties, which override top-level configurations.
In your chart, you write base.mark_point(color='green'), where base contains a color encoding which overrides the mark property. If you don't derive the layer from base (so that it does not have a color encoding), then the line will be green as you hoped. Something like this:
base = alt.Chart(inv.loc['2000':].reset_index(), title=f"usa total inventory")
inventory = base.mark_line().encode(
x='month',
y="inventory",
color="year(date):N"
)
joe = base.mark_line(color='green').encode(
x='month',
y=alt.Y('inventory_zj', scale=alt.Scale(zero=False))
)
inventory + joe