带有 pandas 分组数据的seaborn中的多个单图 [英] Multiple single plots in seaborn with pandas groupby data
问题描述
我想我的问题非常具体,但我似乎找不到合适的解决方案,而且我对得到的错误输出一无所知.无论如何,我有一个从 sqlite 数据库加载的 Pandas 数据框.
My issue is very specific, i guess, but i can't seem to find a proper solution, and im clueless with the error output that i get. Anyway, i have a pandas dataframe loaded from an sqlite database.
data_frame = pd.read_sql_query(
"SELECT (total_comb + total_comb_rc) as total_comb, p_val, w_length from {tn}".format(
tn=table_name), conn)
加载后,我按w_length"值对数据进行分组.
With that loaded, i group the data by the 'w_length' value.
for i, group in data_frame.groupby('w_length'):
现在,我想为使用 seaborn lmplot 创建的每个组绘制散点图.
Now, i want to plot a scatter plot for each group created with seaborn lmplot.
for i, group in data_frame.groupby('w_length'):
sns.lmplot(x=group['total_comb'], y=group['p_val'],
data=group,
fit_reg=False)
sns.despine()
plt.savefig('test_scatter'+i+'.png', dpi=400)
但由于某种原因,我得到了这个输出.
But for some reason im getting, this output.
'[ 6.95485628e-02 3.53641178e-01 3.46862200e+06 4.11684800e+06] not in index'
并且没有绘图文件.我知道我做错了什么,但我似乎无法弄清楚.
and no plot file. I know im doing something wrong, but i cant seem to figure it out.
pd:我知道我可以做这样的事情.
pd: i know i can do something like this.
sns.lmplot(x='total_comb', y='p_val',
data=data_frame,
fit_reg=False,
hue="w_length", x_jitter=.1, col="w_length", col_wrap=3, size=4)
但我还需要每个w_length"的独立图.
but i also need the separeted plots for each 'w_length'.
谢谢!!
推荐答案
假设问题不是因为从 sql 数据库收集数据,可能是因为您调用了sns.lmplot(x=group['total_comb'], y=group['p_val'], data=group)
而不是sns.lmplot(x='total_comb', y='p_val', data=group)
Supposing the problem is not due to the data collection from the sql database, it's probably due to the fact that you call
sns.lmplot(x=group['total_comb'], y=group['p_val'], data=group)
instead of
sns.lmplot(x='total_comb', y='p_val', data=group)
这是一个工作示例,它生成两个单独的图:
Here is a working example, which produces two separate plots:
import pandas as pd
import matplotlib.pyplot as plt
import seaborn as sns
import numpy as np; np.random.seed(42)
x = np.arange(24)
y = np.random.randint(1,10, len(x))
cat = np.random.choice(["A", "B"], size=len(x))
df = pd.DataFrame({"x": x, "y": y, "cat": cat})
for i, group in df.groupby('cat'):
sns.lmplot(x="x", y="y", data=group, fit_reg=False)
plt.savefig(__file__+str(i)+".png")
plt.show()
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