Making a regression line through a bar char using pandas or seaborn

问题

I am new to Pandas and Seaborn and trying to learn. I am trying to add a trend line and a bar plot on the same graph. I have some data that looks like

Year     Sample Size
 2000      500
 2001      3000
 2003      10000
 2004      20000
 2004      23000

I am new to pandas and seaborn and I am attempting to draw a line through the bar plot showing a decreasing or an increasing trend but struggling to do it on the same graph. Till now, I have a bar plot. Below you can find the code.

sampleSizes['Sample Size'] -> is the column I am plotting. It has about 12 values for 12 years.

plt.figure()
ax = sampleSizes['Sample Size'].plot(kind='bar', title="Trend of Sample Sizes", figsize=(15, 10), legend=True, color = 'grey', fontsize=8)
plt.show()

I am struggling to add a trend line to this. I would be grateful if someone could point me in the right direction.

UPDATE

FinancialYear  Sample Size
   2001         2338
   2002         3171
   2003         2597
   2004         2740
   2005         3447
   2006         3098
   2007         2610
   2008         2819
   2009         2057
   2010         2174
   2011         2709

enter code here

回答1:

UPDATE2: using updated data set

In [250]: lr = Ridge()

In [251]: lr.fit(df[['FinancialYear']], df['Sample Size'])
Out[251]:
Ridge(alpha=1.0, copy_X=True, fit_intercept=True, max_iter=None,
   normalize=False, random_state=None, solver='auto', tol=0.001)

In [252]: plt.bar(df['FinancialYear'], df['Sample Size'])
Out[252]: <Container object of 11 artists>

In [253]: plt.plot(df['FinancialYear'], lr.coef_*df['FinancialYear']+lr.intercept_, color='orange')
Out[253]: [<matplotlib.lines.Line2D at 0x171def60>]

Result:

UPDATE:

In [184]: from sklearn.linear_model import Ridge

In [185]: lr = Ridge()

In [186]: lr.fit(df[['Year']], df['Sample Size'])
Out[186]:
Ridge(alpha=1.0, copy_X=True, fit_intercept=True, max_iter=None,
   normalize=False, random_state=None, solver='auto', tol=0.001)

In [187]: plt.bar(df['Year'], df['Sample Size'])
Out[187]: <Container object of 5 artists>

In [188]: plt.plot(df['Year'], lr.coef_*df['Year']+lr.intercept_, color='orange')
Out[188]: [<matplotlib.lines.Line2D at 0x17062898>]

Result:

Try to use matplotlib methods for that:

plt.bar(df['Year'], df['Sample Size'])
plt.plot(df['Year'], df['Sample Size'], '-o', color='orange')

Result:

来源：https://stackoverflow.com/questions/48842293/making-a-regression-line-through-a-bar-char-using-pandas-or-seaborn

标签

python

pandas

matplotlib

seaborn

trendline