# Python
ax.set_ylim([-30, 10])
ax.spines['right'].set_color('none')
ax.spines['top'].set_color('none')

# Julia
ax.set_ylim([-30,10])
ax.spines["top"].set_color("none") # Remove the top axis boundary
ax.spines["right"].set_color("none") # Remove the right axis boundary

# Python
from matplotlib.dates import MonthLocator, WeekdayLocator, DateFormatter
majorformatter = DateFormatter("%d.%m.%Y")
minorformatter = DateFormatter("%H:%M")
majorlocator = DayLocator(interval=1)
minorlocator = HourLocator(byhour=(8,16)) # Not sure about this one

# Julia
majorformatter = matplotlib.dates.DateFormatter("%d.%m.%Y")
minorformatter = matplotlib.dates.DateFormatter("%H:%M")
majorlocator = matplotlib.dates.DayLocator(interval=1)
minorlocator = matplotlib.dates.HourLocator(byhour=(8, 16))

# After an axis exists
ax1.xaxis.set_major_formatter(majorformatter)
ax1.xaxis.set_minor_formatter(minorformatter)
ax1.xaxis.set_major_locator(majorlocator)
ax1.xaxis.set_minor_locator(minorlocator)

using PyPlot
ioff() # Interactive plotting OFF, necessary for inline plotting in IJulia
x = collect(1:10)
y = 10rand(10,1)

p = plot(x,y)
xlabel("X")
ylabel("Y")
PyPlot.title("Your Title Goes Here")
grid("on")
gcf() # Needed by IJulia to display plot

p = plot_date(x,y,linestyle="-",marker="None",label="Base Plot") # Basic line plot

annotate("Look, data!",
    xy=[x;y,# Arrow tip
    xytext=[x+dx;y+dy], # Text offset from tip
    xycoords="data", # Coordinates in in "data" units
    arrowprops=["facecolor"=>"black"]) # Julia dictionary objects are automatically converted to Python object when they pass into a PyPlot function

annotate(L"$\int x = \frac{x^2}{2} + C$",
    xy=[1;0],
    xycoords="axes fraction",
    xytext=[-10,10],
    textcoords="offset points",
    fontsize=30.0,
    ha="right",
    va="bottom")

majorformatter = matplotlib.dates.DateFormatter("%d.%m.%Y")
minorformatter = matplotlib.dates.DateFormatter("%H:%M")
majorlocator = matplotlib.dates.DayLocator(interval=1)
minorlocator = matplotlib.dates.HourLocator(byhour=(8, 16))

ax1.xaxis.set_major_formatter(majorformatter)
ax1.xaxis.set_minor_formatter(minorformatter)
ax1.xaxis.set_major_locator(majorlocator)
ax1.xaxis.set_minor_locator(minorlocator)

subplot(313) # Create the third plot of a 3x1 group of subplots

suptitle("3x1 Subplot") # Supe title, title for all subplots combined

ax = axes(polar="true") # Create a polar axis
# Do your plotting

# Optional changes
ax.set_thetagrids(collect(0:dtheta:360-dtheta)) # Show grid lines from 0 to 360 in increments of dtheta
ax.set_theta_zero_location("N") # Set 0 degrees to the top of the plot
ax.set_theta_direction(-1) # Switch to clockwise
fig.canvas.draw() # Update the figure, required when doing additional modifications

h = plt.hist(x,nbins) # Histogram, PyPlot.plt required to differentiate with conflicting hist command

b = bar(x,y,color="#0f87bf",align="center",alpha=0.4)

b = barh(x,y,color="#0f87bf",align="center",alpha=0.4)

errorbar(x, # Original x data points, N values
    y, # Original y data points, N values
    yerr=errs, # Plus/minus error ranges, Nx2 values
    fmt="o") # Format

xkcd() # Set to XKCD mode, based on the comic (hand drawn)
# Plot everything

p = pie(sizes,
    labels=labels,
    shadow=true,
    startangle=90,
    explode=explode,
    colors=colors,
    autopct="%1.1f%%")

scatter(x,y,s=areas,alpha=0.5)

boxplot(data, # Each column/cell is one box
    notch=true, # Notched center
    whis=0.75, # Whisker length as a percent of inner quartile range
    widths=0.25, # Width of boxes
    vert=false, # Horizontal boxes
    sym="rs") # Symbol color and shape (rs = red square)

###########################
#  Set the tick interval  #
###########################
Mx = matplotlib.ticker.MultipleLocator(20) # Define interval of major ticks
f = matplotlib.ticker.FormatStrFormatter("%1.2f") # Define format of tick labels
ax.xaxis.set_major_locator(Mx) # Set interval of major ticks
ax.xaxis.set_major_formatter(f) # Set format of tick labels

mx = matplotlib.ticker.MultipleLocator(5) # Define interval of minor ticks
ax.xaxis.set_minor_locator(mx) # Set interval of minor ticks

My = matplotlib.ticker.MultipleLocator(0.5) # Define interval of major ticks
ax.yaxis.set_major_locator(My) # Set interval of major ticks

my = matplotlib.ticker.MultipleLocator(0.1) # Define interval of minor ticks
ax.yaxis.set_minor_locator(my) # Set interval of minor ticks

#########################
#  Set tick dimensions  #
#########################
ax.xaxis.set_tick_params(which="major",length=10,width=2)
ax.xaxis.set_tick_params(which="minor",length=5,width=2)

fig.canvas.draw() # Update the figure

################
#  Other Axes  #
################
new_position = [0.06;0.06;0.77;0.91] # Position Method 2
ax.set_position(new_position) # Position Method 2: Change the size and position of the axis
#fig.subplots_adjust(right=0.85) # Position Method 1

ax2 = ax.twinx() # Create another axis on top of the current axis
font2 = Dict("color"=>"purple")
ylabel("Right Axis",fontdict=font2)
p = plot(x,y2,color="purple",linestyle="-",marker="o",label="Second") # Plot a basic line
ax2.set_position(new_position) # Position Method 2
setp(ax2.get_yticklabels(),color="purple") # Y Axis font formatting

ax3 = ax.twinx() # Create another axis on top of the current axis
ax3.spines["right"].set_position(("axes",1.12)) # Offset the y-axis label from the axis itself so it doesn't overlap the second axis
font3 = Dict("color"=>"green")
ylabel("Far Right Axis",fontdict=font3)
p = plot(x,y3,color="green",linestyle="-",marker="o",label="Third") # Plot a basic line
ax3.set_position(new_position) # Position Method 2
setp(ax.get_yticklabels(),color="green") # Y Axis font formatting

axis("tight")

# Enable just the right part of the frame
ax3.set_frame_on(true) # Make the entire frame visible
ax3.patch.set_visible(false) # Make the patch (background) invisible so it doesn't cover up the other axes' plots
ax3.spines["top"].set_visible(false) # Hide the top edge of the axis
ax3.spines["bottom"].set_visible(false) # Hide the bottom edge of the axis

fig.canvas.draw() # Update the figure

ax.spines["top"].set_visible(false) # Hide the top edge of the axis
ax.spines["right"].set_visible(false) # Hide the right edge of the axis
ax.spines["left"].set_position("center") # Move the right axis to the center
ax.spines["bottom"].set_position("center") # Most the bottom axis to the center
ax.xaxis.set_ticks_position("bottom") # Set the x-ticks to only the bottom
ax.yaxis.set_ticks_position("left") # Set the y-ticks to only the left

ax2.spines["top"].set_visible(false) # Hide the top edge of the axis
ax2.spines["right"].set_visible(false) # Hide the right edge of the axis
ax2.xaxis.set_ticks_position("bottom")
ax2.yaxis.set_ticks_position("left")
ax2.spines["left"].set_position(("axes",-0.03)) # Offset the left scale from the axis
ax2.spines["bottom"].set_position(("axes",-0.05)) # Offset the bottom scale from the axis

plot_surface(xgrid, ygrid, z, rstride=2,edgecolors="k", cstride=2, cmap=ColorMap("gray"), alpha=0.8, linewidth=0.25)

contour(xgrid, ygrid, z, colors="black", linewidth=2.0)

axes_grid1 = pyimport("mpl_toolkits.axes_grid1")

divider = axes_grid1.make_axes_locatable(ax)
ax2 = divider.new_vertical(size="100%", pad=0.1)
fig.add_axes(ax2)

ax.spines["top"].set_visible(false)

ax2.spines["bottom"].set_visible(false)

# Upper Line Break Markings
d = 0.015  # how big to make the diagonal lines in axes coordinates
ax2.plot((-d, +d), (-d, +d), transform=ax2.transAxes, color="k", clip_on=false,linewidth=0.8)        # Left diagonal
ax2.plot((1 - d, 1 + d), (-d, +d), transform=ax2.transAxes, color="k", clip_on=false,linewidth=0.8)  # Right diagonal

# Lower Line Break Markings
ax.plot((-d, +d), (1 - d, 1 + d), transform=ax.transAxes, color="k", clip_on=false,linewidth=0.8)  # Left diagonal
ax.plot((1 - d, 1 + d), (1 - d, 1 + d), transform=ax.transAxes, color="k", clip_on=false,linewidth=0.8)  # Right diagonal