Line chart with shaded areas
I tried to make a line chart while having shaded areas to indicate anomalies (recessions in this case). The rate is the variable for the line chart. I created a dummy variable, normal, to indicate if it is normal or not. I want the bar chart to be grey every period when normal = 1, similar to this chart.
This is my code so far. It is very different from what I desired. I wonder if someone can help me out.
df = pd.DataFrame({
'rate' : [90,40,30,30,30,25,25,20,15,10],
'group' : [1,2,3,4,5,6,7,8,9,10],
'normal' : [1,0,0,0,0,1,0,1,0,0]})
ax = df[['group','rate']].plot()
df[['group','normal']].plot(kind = 'bar',secondary_y = True, ax = ax)
plt.show()
python
asked Nov 16 '18 at 20:14
Roger
6411
add a comment |
I tried to make a line chart while having shaded areas to indicate anomalies (recessions in this case). The rate is the variable for the line chart. I created a dummy variable, normal, to indicate if it is normal or not. I want the bar chart to be grey every period when normal = 1, similar to this chart.
This is my code so far. It is very different from what I desired. I wonder if someone can help me out.
df = pd.DataFrame({
'rate' : [90,40,30,30,30,25,25,20,15,10],
'group' : [1,2,3,4,5,6,7,8,9,10],
'normal' : [1,0,0,0,0,1,0,1,0,0]})
ax = df[['group','rate']].plot()
df[['group','normal']].plot(kind = 'bar',secondary_y = True, ax = ax)
plt.show()
python
asked Nov 16 '18 at 20:14
Roger
6411
add a comment |
I tried to make a line chart while having shaded areas to indicate anomalies (recessions in this case). The rate is the variable for the line chart. I created a dummy variable, normal, to indicate if it is normal or not. I want the bar chart to be grey every period when normal = 1, similar to this chart.
This is my code so far. It is very different from what I desired. I wonder if someone can help me out.
df = pd.DataFrame({
'rate' : [90,40,30,30,30,25,25,20,15,10],
'group' : [1,2,3,4,5,6,7,8,9,10],
'normal' : [1,0,0,0,0,1,0,1,0,0]})
ax = df[['group','rate']].plot()
df[['group','normal']].plot(kind = 'bar',secondary_y = True, ax = ax)
plt.show()
python
asked Nov 16 '18 at 20:14
Roger
6411
I tried to make a line chart while having shaded areas to indicate anomalies (recessions in this case). The rate is the variable for the line chart. I created a dummy variable, normal, to indicate if it is normal or not. I want the bar chart to be grey every period when normal = 1, similar to this chart.
This is my code so far. It is very different from what I desired. I wonder if someone can help me out.
df = pd.DataFrame({
'rate' : [90,40,30,30,30,25,25,20,15,10],
'group' : [1,2,3,4,5,6,7,8,9,10],
'normal' : [1,0,0,0,0,1,0,1,0,0]})
ax = df[['group','rate']].plot()
df[['group','normal']].plot(kind = 'bar',secondary_y = True, ax = ax)
plt.show()
python
python
asked Nov 16 '18 at 20:14
Roger
6411
asked Nov 16 '18 at 20:14
Roger
6411
asked Nov 16 '18 at 20:14
Roger
6411
asked Nov 16 '18 at 20:14
Roger
6411
asked Nov 16 '18 at 20:14
Roger
6411
6411
add a comment |
add a comment |
1 Answer
1
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IIUC, and based on the question you linked, you could just find your group values where normal == 1, and use ax.vline to draw a thick line at each of those points. For example:
ax = df.set_index('group')['rate'].plot()
x = df.loc[df.normal == 1, 'group']
for i in x:
ax.axvline(i, color='gray', alpha = 0.5, linewidth=30)
plt.show()
answered Nov 16 '18 at 20:30
sacul
29.9k41740
add a comment |
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1 Answer
1
active
oldest
votes
1 Answer
1
active
oldest
votes
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oldest
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active
oldest
votes
IIUC, and based on the question you linked, you could just find your group values where normal == 1, and use ax.vline to draw a thick line at each of those points. For example:
ax = df.set_index('group')['rate'].plot()
x = df.loc[df.normal == 1, 'group']
for i in x:
ax.axvline(i, color='gray', alpha = 0.5, linewidth=30)
plt.show()
answered Nov 16 '18 at 20:30
sacul
29.9k41740
add a comment |
IIUC, and based on the question you linked, you could just find your group values where normal == 1, and use ax.vline to draw a thick line at each of those points. For example:
ax = df.set_index('group')['rate'].plot()
x = df.loc[df.normal == 1, 'group']
for i in x:
ax.axvline(i, color='gray', alpha = 0.5, linewidth=30)
plt.show()
answered Nov 16 '18 at 20:30
sacul
29.9k41740
add a comment |
IIUC, and based on the question you linked, you could just find your group values where normal == 1, and use ax.vline to draw a thick line at each of those points. For example:
ax = df.set_index('group')['rate'].plot()
x = df.loc[df.normal == 1, 'group']
for i in x:
ax.axvline(i, color='gray', alpha = 0.5, linewidth=30)
plt.show()
answered Nov 16 '18 at 20:30
sacul
29.9k41740
IIUC, and based on the question you linked, you could just find your group values where normal == 1, and use ax.vline to draw a thick line at each of those points. For example:
ax = df.set_index('group')['rate'].plot()
x = df.loc[df.normal == 1, 'group']
for i in x:
ax.axvline(i, color='gray', alpha = 0.5, linewidth=30)
plt.show()
answered Nov 16 '18 at 20:30
sacul
29.9k41740
answered Nov 16 '18 at 20:30
sacul
29.9k41740
answered Nov 16 '18 at 20:30
sacul
29.9k41740
answered Nov 16 '18 at 20:30
sacul
29.9k41740
29.9k41740
add a comment |
add a comment |
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