Mixing
Stripplot and lineplot weird result
When I use lineplot or stripplot it works well. But using both the median is shifted; I don't understand why! Thank you for your help.
sns.lineplot(x='quality', y='alcohol', data=df, estimator=np.median, err_style=None)
sns.stripplot(x='quality', y='alcohol', data=df, jitter=True, color='red', alpha=0.2, edgecolor='none')
stripplot
lineplot+stripplot
lineplot
python seaborn
edited Jan 1 at 13:23
Scott Boston
56.1k73157
asked Dec 31 '18 at 10:55
hgangerhganger
143
add a comment |
When I use lineplot or stripplot it works well. But using both the median is shifted; I don't understand why! Thank you for your help.
sns.lineplot(x='quality', y='alcohol', data=df, estimator=np.median, err_style=None)
sns.stripplot(x='quality', y='alcohol', data=df, jitter=True, color='red', alpha=0.2, edgecolor='none')
stripplot
lineplot+stripplot
lineplot
python seaborn
edited Jan 1 at 13:23
Scott Boston
56.1k73157
asked Dec 31 '18 at 10:55
hgangerhganger
143
add a comment |
When I use lineplot or stripplot it works well. But using both the median is shifted; I don't understand why! Thank you for your help.
sns.lineplot(x='quality', y='alcohol', data=df, estimator=np.median, err_style=None)
sns.stripplot(x='quality', y='alcohol', data=df, jitter=True, color='red', alpha=0.2, edgecolor='none')
stripplot
lineplot+stripplot
lineplot
python seaborn
edited Jan 1 at 13:23
Scott Boston
56.1k73157
asked Dec 31 '18 at 10:55
hgangerhganger
143
When I use lineplot or stripplot it works well. But using both the median is shifted; I don't understand why! Thank you for your help.
sns.lineplot(x='quality', y='alcohol', data=df, estimator=np.median, err_style=None)
sns.stripplot(x='quality', y='alcohol', data=df, jitter=True, color='red', alpha=0.2, edgecolor='none')
stripplot
lineplot+stripplot
lineplot
python seaborn
python seaborn
edited Jan 1 at 13:23
Scott Boston
56.1k73157
asked Dec 31 '18 at 10:55
hgangerhganger
143
edited Jan 1 at 13:23
Scott Boston
56.1k73157
asked Dec 31 '18 at 10:55
hgangerhganger
143
edited Jan 1 at 13:23
Scott Boston
56.1k73157
edited Jan 1 at 13:23
Scott Boston
56.1k73157
edited Jan 1 at 13:23
Scott Boston
56.1k73157
56.1k73157
asked Dec 31 '18 at 10:55
hgangerhganger
143
asked Dec 31 '18 at 10:55
hgangerhganger
143
asked Dec 31 '18 at 10:55
hgangerhganger
143
143
add a comment |
add a comment |
1 Answer
1
active
oldest
votes
What is happening here is that your first plot is creating an x axis with 0 to n range, and relabeling those x tick with a list of integers from 3 to n, then when the second chart or the stripplot plots on top of this x axis it is using the original number therefore xtick 3 for this new chart starts on labelled xtick 6. Hence the offset.
One way to do correct this is to create a xaxis with a predefined range and then plot both charts on this predefined scale, see example below:
import seaborn as sns
import matplotlib.pyplot as plt
x = [3,4,5,6,7,8]
y = [10, 12, 15, 18, 19, 26]
#First axes creates the error in graphing
fig, ax = plt.subplots(1,2)
sns.lineplot(x=x,y=y, ax=ax[0])
sns.stripplot(x=x, y=y, ax=ax[0])
#Second axes shows correction
xplot = range(len(x))
sns.lineplot(x=xplot,y=y, ax=ax[1])
sns.stripplot(x, y=y, ax=ax[1])
Output:
answered Jan 1 at 4:53
Scott BostonScott Boston
56.1k73157
Thank you. However I don't understand how to apply it. I've a file with 4898 rows with 7 qualities and lineplot compute the median value (of alcohol variable) for each quality.
– hganger
Jan 1 at 10:17
1
Finally, I did it thanks to your post and the offset idea. labels, uniques = pd.factorize(df['quality'], sort = True) sns.lineplot(x=labels, y=df['alcohol'], estimator=np.median, err_style=None, color='black') sns.stripplot(x='quality', y='alcohol', data=df, jitter=True, color='red', alpha=0.2, edgecolor='none')
– hganger
Jan 1 at 10:35
add a comment |
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1 Answer
1
active
oldest
votes
1 Answer
1
active
oldest
votes
active
oldest
votes
active
oldest
votes
What is happening here is that your first plot is creating an x axis with 0 to n range, and relabeling those x tick with a list of integers from 3 to n, then when the second chart or the stripplot plots on top of this x axis it is using the original number therefore xtick 3 for this new chart starts on labelled xtick 6. Hence the offset.
One way to do correct this is to create a xaxis with a predefined range and then plot both charts on this predefined scale, see example below:
import seaborn as sns
import matplotlib.pyplot as plt
x = [3,4,5,6,7,8]
y = [10, 12, 15, 18, 19, 26]
#First axes creates the error in graphing
fig, ax = plt.subplots(1,2)
sns.lineplot(x=x,y=y, ax=ax[0])
sns.stripplot(x=x, y=y, ax=ax[0])
#Second axes shows correction
xplot = range(len(x))
sns.lineplot(x=xplot,y=y, ax=ax[1])
sns.stripplot(x, y=y, ax=ax[1])
Output:
answered Jan 1 at 4:53
Scott BostonScott Boston
56.1k73157
Thank you. However I don't understand how to apply it. I've a file with 4898 rows with 7 qualities and lineplot compute the median value (of alcohol variable) for each quality.
– hganger
Jan 1 at 10:17
1
Finally, I did it thanks to your post and the offset idea. labels, uniques = pd.factorize(df['quality'], sort = True) sns.lineplot(x=labels, y=df['alcohol'], estimator=np.median, err_style=None, color='black') sns.stripplot(x='quality', y='alcohol', data=df, jitter=True, color='red', alpha=0.2, edgecolor='none')
– hganger
Jan 1 at 10:35
add a comment |
What is happening here is that your first plot is creating an x axis with 0 to n range, and relabeling those x tick with a list of integers from 3 to n, then when the second chart or the stripplot plots on top of this x axis it is using the original number therefore xtick 3 for this new chart starts on labelled xtick 6. Hence the offset.
One way to do correct this is to create a xaxis with a predefined range and then plot both charts on this predefined scale, see example below:
import seaborn as sns
import matplotlib.pyplot as plt
x = [3,4,5,6,7,8]
y = [10, 12, 15, 18, 19, 26]
#First axes creates the error in graphing
fig, ax = plt.subplots(1,2)
sns.lineplot(x=x,y=y, ax=ax[0])
sns.stripplot(x=x, y=y, ax=ax[0])
#Second axes shows correction
xplot = range(len(x))
sns.lineplot(x=xplot,y=y, ax=ax[1])
sns.stripplot(x, y=y, ax=ax[1])
Output:
answered Jan 1 at 4:53
Scott BostonScott Boston
56.1k73157
Thank you. However I don't understand how to apply it. I've a file with 4898 rows with 7 qualities and lineplot compute the median value (of alcohol variable) for each quality.
– hganger
Jan 1 at 10:17
1
Finally, I did it thanks to your post and the offset idea. labels, uniques = pd.factorize(df['quality'], sort = True) sns.lineplot(x=labels, y=df['alcohol'], estimator=np.median, err_style=None, color='black') sns.stripplot(x='quality', y='alcohol', data=df, jitter=True, color='red', alpha=0.2, edgecolor='none')
– hganger
Jan 1 at 10:35
add a comment |
What is happening here is that your first plot is creating an x axis with 0 to n range, and relabeling those x tick with a list of integers from 3 to n, then when the second chart or the stripplot plots on top of this x axis it is using the original number therefore xtick 3 for this new chart starts on labelled xtick 6. Hence the offset.
One way to do correct this is to create a xaxis with a predefined range and then plot both charts on this predefined scale, see example below:
import seaborn as sns
import matplotlib.pyplot as plt
x = [3,4,5,6,7,8]
y = [10, 12, 15, 18, 19, 26]
#First axes creates the error in graphing
fig, ax = plt.subplots(1,2)
sns.lineplot(x=x,y=y, ax=ax[0])
sns.stripplot(x=x, y=y, ax=ax[0])
#Second axes shows correction
xplot = range(len(x))
sns.lineplot(x=xplot,y=y, ax=ax[1])
sns.stripplot(x, y=y, ax=ax[1])
Output:
answered Jan 1 at 4:53
Scott BostonScott Boston
56.1k73157
What is happening here is that your first plot is creating an x axis with 0 to n range, and relabeling those x tick with a list of integers from 3 to n, then when the second chart or the stripplot plots on top of this x axis it is using the original number therefore xtick 3 for this new chart starts on labelled xtick 6. Hence the offset.
One way to do correct this is to create a xaxis with a predefined range and then plot both charts on this predefined scale, see example below:
import seaborn as sns
import matplotlib.pyplot as plt
x = [3,4,5,6,7,8]
y = [10, 12, 15, 18, 19, 26]
#First axes creates the error in graphing
fig, ax = plt.subplots(1,2)
sns.lineplot(x=x,y=y, ax=ax[0])
sns.stripplot(x=x, y=y, ax=ax[0])
#Second axes shows correction
xplot = range(len(x))
sns.lineplot(x=xplot,y=y, ax=ax[1])
sns.stripplot(x, y=y, ax=ax[1])
Output:
answered Jan 1 at 4:53
Scott BostonScott Boston
56.1k73157
answered Jan 1 at 4:53
Scott BostonScott Boston
56.1k73157
answered Jan 1 at 4:53
Scott BostonScott Boston
56.1k73157
answered Jan 1 at 4:53
Scott BostonScott Boston
56.1k73157
56.1k73157
Thank you. However I don't understand how to apply it. I've a file with 4898 rows with 7 qualities and lineplot compute the median value (of alcohol variable) for each quality.
– hganger
Jan 1 at 10:17
1
Finally, I did it thanks to your post and the offset idea. labels, uniques = pd.factorize(df['quality'], sort = True) sns.lineplot(x=labels, y=df['alcohol'], estimator=np.median, err_style=None, color='black') sns.stripplot(x='quality', y='alcohol', data=df, jitter=True, color='red', alpha=0.2, edgecolor='none')
– hganger
Jan 1 at 10:35
add a comment |
Thank you. However I don't understand how to apply it. I've a file with 4898 rows with 7 qualities and lineplot compute the median value (of alcohol variable) for each quality.
– hganger
Jan 1 at 10:17
1
Finally, I did it thanks to your post and the offset idea. labels, uniques = pd.factorize(df['quality'], sort = True) sns.lineplot(x=labels, y=df['alcohol'], estimator=np.median, err_style=None, color='black') sns.stripplot(x='quality', y='alcohol', data=df, jitter=True, color='red', alpha=0.2, edgecolor='none')
– hganger
Jan 1 at 10:35
Thank you. However I don't understand how to apply it. I've a file with 4898 rows with 7 qualities and lineplot compute the median value (of alcohol variable) for each quality.
– hganger
Jan 1 at 10:17
Thank you. However I don't understand how to apply it. I've a file with 4898 rows with 7 qualities and lineplot compute the median value (of alcohol variable) for each quality.
– hganger
Jan 1 at 10:17
1
1
Finally, I did it thanks to your post and the offset idea. labels, uniques = pd.factorize(df['quality'], sort = True) sns.lineplot(x=labels, y=df['alcohol'], estimator=np.median, err_style=None, color='black') sns.stripplot(x='quality', y='alcohol', data=df, jitter=True, color='red', alpha=0.2, edgecolor='none')
– hganger
Jan 1 at 10:35
Finally, I did it thanks to your post and the offset idea. labels, uniques = pd.factorize(df['quality'], sort = True) sns.lineplot(x=labels, y=df['alcohol'], estimator=np.median, err_style=None, color='black') sns.stripplot(x='quality', y='alcohol', data=df, jitter=True, color='red', alpha=0.2, edgecolor='none')
– hganger
Jan 1 at 10:35
add a comment |
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