Why does this plot fail when adding scatter but it works when removing it?
I am using the following to plot a x date and y decimal. It works great without the commented line (scatter), but if you uncomment it it shows all in one x axis
what am I missing?
thanks
import matplotlib.pyplot as plt
import datetime
fig = plt.figure(facecolor="#979899")
ax = plt.gca()
ax.set_facecolor("#d1d1d1")
plt.grid(True)
plt.title("This is a title",fontsize=16)
plt.xticks([datetime.date(2018,11,20),datetime.date(2018,11,21),datetime.date(2018,11,22)],["11/20","11/21","11/22"])
plt.yticks([0.0,0.1,0.2,0.3,0.4,0.5,0.6,0.7,0.8,0.9,1.0],["0.0","0.1","0.2","0.3","0.4","0.5","0.6","0.7","0.8","0.9","1.0"])
x1 = [datetime.date(2018,11,20),datetime.date(2018,11,21),datetime.date(2018,11,22)]
y1 = [0.18,0.32,0.21]
for i,item in enumerate(y1):
xP = x1[i]
yP = y1[i]
plt.text(xP,yP,str(item)+"%",fontsize=11)
#plt.scatter(x1,y1)
plt.plot(x1,y1)
plt.show()
python matplotlib
add a comment |
I am using the following to plot a x date and y decimal. It works great without the commented line (scatter), but if you uncomment it it shows all in one x axis
what am I missing?
thanks
import matplotlib.pyplot as plt
import datetime
fig = plt.figure(facecolor="#979899")
ax = plt.gca()
ax.set_facecolor("#d1d1d1")
plt.grid(True)
plt.title("This is a title",fontsize=16)
plt.xticks([datetime.date(2018,11,20),datetime.date(2018,11,21),datetime.date(2018,11,22)],["11/20","11/21","11/22"])
plt.yticks([0.0,0.1,0.2,0.3,0.4,0.5,0.6,0.7,0.8,0.9,1.0],["0.0","0.1","0.2","0.3","0.4","0.5","0.6","0.7","0.8","0.9","1.0"])
x1 = [datetime.date(2018,11,20),datetime.date(2018,11,21),datetime.date(2018,11,22)]
y1 = [0.18,0.32,0.21]
for i,item in enumerate(y1):
xP = x1[i]
yP = y1[i]
plt.text(xP,yP,str(item)+"%",fontsize=11)
#plt.scatter(x1,y1)
plt.plot(x1,y1)
plt.show()
python matplotlib
add a comment |
I am using the following to plot a x date and y decimal. It works great without the commented line (scatter), but if you uncomment it it shows all in one x axis
what am I missing?
thanks
import matplotlib.pyplot as plt
import datetime
fig = plt.figure(facecolor="#979899")
ax = plt.gca()
ax.set_facecolor("#d1d1d1")
plt.grid(True)
plt.title("This is a title",fontsize=16)
plt.xticks([datetime.date(2018,11,20),datetime.date(2018,11,21),datetime.date(2018,11,22)],["11/20","11/21","11/22"])
plt.yticks([0.0,0.1,0.2,0.3,0.4,0.5,0.6,0.7,0.8,0.9,1.0],["0.0","0.1","0.2","0.3","0.4","0.5","0.6","0.7","0.8","0.9","1.0"])
x1 = [datetime.date(2018,11,20),datetime.date(2018,11,21),datetime.date(2018,11,22)]
y1 = [0.18,0.32,0.21]
for i,item in enumerate(y1):
xP = x1[i]
yP = y1[i]
plt.text(xP,yP,str(item)+"%",fontsize=11)
#plt.scatter(x1,y1)
plt.plot(x1,y1)
plt.show()
python matplotlib
I am using the following to plot a x date and y decimal. It works great without the commented line (scatter), but if you uncomment it it shows all in one x axis
what am I missing?
thanks
import matplotlib.pyplot as plt
import datetime
fig = plt.figure(facecolor="#979899")
ax = plt.gca()
ax.set_facecolor("#d1d1d1")
plt.grid(True)
plt.title("This is a title",fontsize=16)
plt.xticks([datetime.date(2018,11,20),datetime.date(2018,11,21),datetime.date(2018,11,22)],["11/20","11/21","11/22"])
plt.yticks([0.0,0.1,0.2,0.3,0.4,0.5,0.6,0.7,0.8,0.9,1.0],["0.0","0.1","0.2","0.3","0.4","0.5","0.6","0.7","0.8","0.9","1.0"])
x1 = [datetime.date(2018,11,20),datetime.date(2018,11,21),datetime.date(2018,11,22)]
y1 = [0.18,0.32,0.21]
for i,item in enumerate(y1):
xP = x1[i]
yP = y1[i]
plt.text(xP,yP,str(item)+"%",fontsize=11)
#plt.scatter(x1,y1)
plt.plot(x1,y1)
plt.show()
python matplotlib
python matplotlib
asked Nov 24 '18 at 3:06
RollRollRollRoll
3,3981353113
3,3981353113
add a comment |
add a comment |
2 Answers
2
active
oldest
votes
The problem is the autoscaling of Collections. This is the underlying issue, which is long known, but hard to come by. There are certain cases, where autoscaling does not work reliably, when values are too close to each other. This is unfortunately often the case for dates.
import matplotlib.pyplot as plt
import datetime
fig, ax = plt.subplots()
x1 = [datetime.date(2018,11,20),datetime.date(2018,11,22)]
y1 = [1,2]
plt.scatter(x1,y1, s=50, color="red")
plt.plot(x1,y1, marker="o", ms=3, zorder=3)
plt.show()
You can however create a plot
first. This will determine the autoscaling limits sufficiently. After that plot the scatter
.
import matplotlib.pyplot as plt
import datetime
fig, ax = plt.subplots()
x1 = [datetime.date(2018,11,20),datetime.date(2018,11,22)]
y1 = [1,2]
plt.plot(x1,y1, marker="o", ms=3)
plt.scatter(x1,y1, s=50, color="red")
plt.show()
that's a weird bug tks
– RollRoll
Nov 24 '18 at 17:51
add a comment |
try setting the limits for both x and y axes:
plt.scatter(x1,y1)
plt.plot(x1,y1)
plt.xlim(datetime.date(2018,11,20),datetime.date(2018,11,22))
plt.ylim(0.1,0.4)
plt.show()
add a comment |
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2 Answers
2
active
oldest
votes
2 Answers
2
active
oldest
votes
active
oldest
votes
active
oldest
votes
The problem is the autoscaling of Collections. This is the underlying issue, which is long known, but hard to come by. There are certain cases, where autoscaling does not work reliably, when values are too close to each other. This is unfortunately often the case for dates.
import matplotlib.pyplot as plt
import datetime
fig, ax = plt.subplots()
x1 = [datetime.date(2018,11,20),datetime.date(2018,11,22)]
y1 = [1,2]
plt.scatter(x1,y1, s=50, color="red")
plt.plot(x1,y1, marker="o", ms=3, zorder=3)
plt.show()
You can however create a plot
first. This will determine the autoscaling limits sufficiently. After that plot the scatter
.
import matplotlib.pyplot as plt
import datetime
fig, ax = plt.subplots()
x1 = [datetime.date(2018,11,20),datetime.date(2018,11,22)]
y1 = [1,2]
plt.plot(x1,y1, marker="o", ms=3)
plt.scatter(x1,y1, s=50, color="red")
plt.show()
that's a weird bug tks
– RollRoll
Nov 24 '18 at 17:51
add a comment |
The problem is the autoscaling of Collections. This is the underlying issue, which is long known, but hard to come by. There are certain cases, where autoscaling does not work reliably, when values are too close to each other. This is unfortunately often the case for dates.
import matplotlib.pyplot as plt
import datetime
fig, ax = plt.subplots()
x1 = [datetime.date(2018,11,20),datetime.date(2018,11,22)]
y1 = [1,2]
plt.scatter(x1,y1, s=50, color="red")
plt.plot(x1,y1, marker="o", ms=3, zorder=3)
plt.show()
You can however create a plot
first. This will determine the autoscaling limits sufficiently. After that plot the scatter
.
import matplotlib.pyplot as plt
import datetime
fig, ax = plt.subplots()
x1 = [datetime.date(2018,11,20),datetime.date(2018,11,22)]
y1 = [1,2]
plt.plot(x1,y1, marker="o", ms=3)
plt.scatter(x1,y1, s=50, color="red")
plt.show()
that's a weird bug tks
– RollRoll
Nov 24 '18 at 17:51
add a comment |
The problem is the autoscaling of Collections. This is the underlying issue, which is long known, but hard to come by. There are certain cases, where autoscaling does not work reliably, when values are too close to each other. This is unfortunately often the case for dates.
import matplotlib.pyplot as plt
import datetime
fig, ax = plt.subplots()
x1 = [datetime.date(2018,11,20),datetime.date(2018,11,22)]
y1 = [1,2]
plt.scatter(x1,y1, s=50, color="red")
plt.plot(x1,y1, marker="o", ms=3, zorder=3)
plt.show()
You can however create a plot
first. This will determine the autoscaling limits sufficiently. After that plot the scatter
.
import matplotlib.pyplot as plt
import datetime
fig, ax = plt.subplots()
x1 = [datetime.date(2018,11,20),datetime.date(2018,11,22)]
y1 = [1,2]
plt.plot(x1,y1, marker="o", ms=3)
plt.scatter(x1,y1, s=50, color="red")
plt.show()
The problem is the autoscaling of Collections. This is the underlying issue, which is long known, but hard to come by. There are certain cases, where autoscaling does not work reliably, when values are too close to each other. This is unfortunately often the case for dates.
import matplotlib.pyplot as plt
import datetime
fig, ax = plt.subplots()
x1 = [datetime.date(2018,11,20),datetime.date(2018,11,22)]
y1 = [1,2]
plt.scatter(x1,y1, s=50, color="red")
plt.plot(x1,y1, marker="o", ms=3, zorder=3)
plt.show()
You can however create a plot
first. This will determine the autoscaling limits sufficiently. After that plot the scatter
.
import matplotlib.pyplot as plt
import datetime
fig, ax = plt.subplots()
x1 = [datetime.date(2018,11,20),datetime.date(2018,11,22)]
y1 = [1,2]
plt.plot(x1,y1, marker="o", ms=3)
plt.scatter(x1,y1, s=50, color="red")
plt.show()
edited Nov 29 '18 at 13:40
answered Nov 24 '18 at 3:23
ImportanceOfBeingErnestImportanceOfBeingErnest
132k13144219
132k13144219
that's a weird bug tks
– RollRoll
Nov 24 '18 at 17:51
add a comment |
that's a weird bug tks
– RollRoll
Nov 24 '18 at 17:51
that's a weird bug tks
– RollRoll
Nov 24 '18 at 17:51
that's a weird bug tks
– RollRoll
Nov 24 '18 at 17:51
add a comment |
try setting the limits for both x and y axes:
plt.scatter(x1,y1)
plt.plot(x1,y1)
plt.xlim(datetime.date(2018,11,20),datetime.date(2018,11,22))
plt.ylim(0.1,0.4)
plt.show()
add a comment |
try setting the limits for both x and y axes:
plt.scatter(x1,y1)
plt.plot(x1,y1)
plt.xlim(datetime.date(2018,11,20),datetime.date(2018,11,22))
plt.ylim(0.1,0.4)
plt.show()
add a comment |
try setting the limits for both x and y axes:
plt.scatter(x1,y1)
plt.plot(x1,y1)
plt.xlim(datetime.date(2018,11,20),datetime.date(2018,11,22))
plt.ylim(0.1,0.4)
plt.show()
try setting the limits for both x and y axes:
plt.scatter(x1,y1)
plt.plot(x1,y1)
plt.xlim(datetime.date(2018,11,20),datetime.date(2018,11,22))
plt.ylim(0.1,0.4)
plt.show()
answered Nov 24 '18 at 3:13
tengteng
842721
842721
add a comment |
add a comment |
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