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How to plot line plot with vertical-based data (well-log)?

I was trying to plot geophysics data (well-log) into a scatter plot in Altair using mark_line function, but the line plot is not connecting the dots/ points from top-bottom, but rather from left-right. If you see figure on the left, the data is distributed vertically as clearly seen, in the middle is the result using mark_line, and on the right is the one I wanted, just flipped the X and Y axis.
Is there any way to make a plot to behave just like left figure, but in line encoding?
Or perhaps some form of hacks to flipped the display on the right figure?
chart1 = alt.Chart(w).mark_point(color='green').encode(
alt.X('GR', scale=alt.Scale(domain=[0,300])),
alt.Y('DEPT', scale=alt.Scale(domain=[7000, 7100])),
).interactive()
chart2 = alt.Chart(w).mark_line(color='green').encode(
alt.X('GR', scale=alt.Scale(domain=[0,300])),
alt.Y('DEPT', scale=alt.Scale(domain=[7000, 7100])),
).interactive()
chart3 = alt.Chart(w).mark_line(color='green').encode(
alt.Y('GR', scale=alt.Scale(domain=[0,300])),
alt.X('DEPT', scale=alt.Scale(domain=[7000, 7100])),
).interactive()
chart1 | chart2 | chart3
Plot using Altair
For those who needs more information, this is a typical dataset from borehole geophysics data/ well-log. Data (GR) is displayed in vertical line, against depth (DEPT).
Thanks for the help!

From what I tested so far, Altair scatters plot using mark_line will always follow the X-axis by default. Therefore, in the case where you want to plot data across Y-axis, one has to specify the order of the connecting line. In the following, I add order = 'DEPT' which was the Y-axis in the plot.
alt.Chart(
w
).mark_line(
color='green',
point=True,
).encode(
alt.X('GR', scale=alt.Scale(domain=[0,250])),
alt.Y('DEPT', sort = 'descending',scale=alt.Scale(domain=[7000, 7030])),
order = 'DEPT' #this has to be added to make sure the plot is following the order of Y-axis, DEPT
).configure_mark(
color = 'red'
).interactive()
Result:

Plot two datasets at same position based on their index

I'm trying to plot two datasets (called Height and Temperature) on different y axes.
Both datasets have the same length.
Both datasets are linked together by a third dataset, RH.
I have tried to use matplotlib to plot the data using twiny() but I am struggling to align both datasets together on the same plot.
Here is the plot I want to align.
The horizontal black line on the figure is defined as the 0°C degree line that was found from Height and was used to test if both datasets, when plotted, would be aligned. They do not. There is a noticable difference between the black line and the 0°C tick from Temperature.
Rather than the two y axes changing independently from each other I would like to plot each index from Height and Temperature at the same y position on the plot.
Here is the code that I used to create the plot:
#Define number of subplots sharing y axis
f, ax1 = plt.subplots()
ax1.minorticks_on()
ax1.grid(which='major',axis='both',c='grey')
#Set axis parameters
ax1.set_ylabel('Height $(km)$')
ax1.set_ylim([np.nanmin(Height), np.nanmax(Height)])
#Plot RH
ax1.plot(RH, Height, label='Original', lw=0.5)
ax1.set_xlabel('RH $(\%)$')
ax2 = ax1.twinx()
ax2.plot(RH, Temperature, label='Original', lw=0.5, c='black')
ax2.set_ylabel('Temperature ($^\circ$C)')
ax2.set_ylim([np.nanmin(Temperature), np.nanmax(Temperature)])
Any help on this would be amazing. Thanks.

Maybe the atmosphere is wrong. :)
It sounds like you are trying to align the two y axes at particular values. Why are you doing this? The relationship of Height vs. Temperature is non-linear, so I think you are setting the stage for a confusing graph. Any particular line you plot can only be interpreted against one vertical axis.
If needed, I think you will be forced to "do some math" on the limits of the y axes. This link may be helpful:
align scales

Is there any way to give matplotlib pie chart a zorder?

I am using the matplotlib pie chart: https://matplotlib.org/api/_as_gen/matplotlib.axes.Axes.pie.html.
I am generating a network diagram that uses these piecharts. I am drawing a line down the middle of the pie chart to delineate two different processes. My problem is that when I draw this line down the middle it will overlay ontop of all piecharts, so if they overlap, the lines will not be layered correctly:
I realize that there is no zorder for the matplotlib pie chart, but is there a way to get it to emulate a zorder? That way I can use the zorder for the line, and then layer a pie chart on top of that line to overlap it.

pie() returns a list of patches. These individual patches have a zorder property, so you could loop over them and adjust their zorder
fig,ax = plt.subplots()
ax.set_aspect('equal')
p1,t1 = plt.pie([50,50], center=(0,0))
p2,t2 = plt.pie([1,1,1,1], center=(1.2,0)) # this pie-chart is over the first one
[p.set_zorder(-1) for p in p2] # change the z-order of the patches so that the
# 2nd pie-chart ends up below the first one

align grid lines on two plots

I have 2 subplots in matplotlib in Python. They are stacked on top of each other.
I want to have gridlines on each plot, which I have done successfully. But each plot has a different x axis and, therefore, the vertical grid lines of the top plot are not aligned with those of the bottom plot.
I would like the grid lines of the top plot to be in the same position on the x axis as they are on the bottom plot i.e. the vertical grid lines in both plots should be aligned.
I imaging that I can tell my grid lines exactly where to be, and so I could achieve my goal by adjusting the lines until they match as well as possible.
I just hoped that there might be some easier way that would just allow me to align the gridlines on both plots.
Edit:
I don't think the shared axis stuff is quite what I want.
My top and bottom plot have very different scales, so when I share the axes, it shifts the scaling too. For example, say my top plot has data that runs from 0-100 on the x axis and on the bottom plot the data runs from 0-50. When I share the axis, the top plot only shows data from 0-50, which I don't want it to.
I want it to show from 0-100 as it did before, but just want it to share the axis and gridlines from the other plot.

You could use LinearLocator:
from matplotlib.ticker import LinearLocator
Then on each of your x-axis or only on one of them call:
N = 6 # Set number of gridlines you want to have in each graph
ax1.xaxis.set_major_locator(LinearLocator(N))
ax2.xaxis.set_major_locator(LinearLocator(N))
Or get the number of ticks from your source axis and set it on target axis:
N = source_ax.xaxis.get_major_ticks()
target_ax.xaxis.set_major_locator(LinearLocator(N))

plotting 2 graph in same window using matplotlib in python

I was plotting a line graph and a bar chart in matplotlib and both individually were working fine with my script.
but i'm facing a problem:
1. if i want to plot both graphs in the same output window
2. if i want to customize the display window to 1024*700
in 1 st case I was using subplot to plot two graphs in same window but i'm not being able to give both graphs their individual x-axis and y-axis names and also their individual title.
my failed code is:
import numpy as np
import matplotlib.mlab as mlab
import matplotlib.pyplot as plt
xs,ys = np.loadtxt("c:/users/name/desktop/new folder/x/counter.cnt",delimiter = ',').T
fig = plt.figure()
lineGraph = fig.add_subplot(211)
barChart = fig.add_subplot(212)
plt.title('DISTRIBUTION of NUMBER')
lineGraph = lineGraph.plot(xs,ys,'-') #generate line graph
barChart = barChart.bar(xs,ys,width=1.0,facecolor='g') #generate bar plot
plt.grid(True)
plt.axis([0,350,0,25]) #controlls axis for charts x first and then y axis.
plt.savefig('new.png',dpi=400)
plt.show()
but with this I am not being able to mark both graphs properly.
and also please site some idea about how to resize the window to 1024*700.

When you say
I was using subplot to plot two graphs in same window but i'm not being able to give both graphs their individual x-axis and y-axis names and also their individual title.
do you mean you want to set axis labels? If so try using lineGraph.set_xlabel and lineGraph.set_ylabel. Alternatively, call plt.xlabel and plot.ylabel just after you create a plot and before you create any other plots. For example
# Line graph subplot
lineGraph = lineGraph.plot(xs,ys,'-')
lineGraph.set_xlabel('x')
lineGraph.set_ylabel('y')
# Bar graph subplot
barChart = barChart.bar(xs,ys,width=1.0,facecolor='g')
barChart.set_xlabel('x')
barChart.set_ylabel('y')
The same applies to the title. Calling plt.title will add a title to the currently active plot. This is the last plot that you created or the last plot you actived with plt.gca. If you want a title on a specific subplot use the subplot handle: lineGraph.set_title or barChart.set_title.

fig.add_subplot returns a matplotlib Axes object. Methods on that object include set_xlabel and set_ylabel, as described by Chris. You can see the full set of methods available on Axes objects at http://matplotlib.sourceforge.net/api/axes_api.html.