如何用seaborn绘制线图？

Question

I have a sample data frame shown below. I want to plot each column against the data frame index.

x1 = pd.DataFrame()
x1['x25'] = df['X'][0:45].reset_index(drop=True)
x1['x50'] = df['X'][90:135].reset_index(drop=True)
x1['x75'] = df['X'][180:225].reset_index(drop=True)
x1['x100'] = df['X'][270:315].reset_index(drop=True)
x1['x125'] = df['X'][360:405].reset_index(drop=True)  

using x1.head() the output is shown below.

    x25      x50      x75    x100   x125
0   22732   22852   22997   23151   23253
1   22732   22853   22995   23153   23254
2   22733   22851   22997   23153   23254
3   22731   22851   22995   23150   23255
4   22730   22851   22997   23152   23254

I checked the output of each column, they are all equal.

print(len(x1.index), len(x1['x25']), len(x1['x50']), len(x1['x75']), len(x1['x100']), len(x1['x125']))

45 45 45 45 45 45

I am trying to plot with the command below, but i am getting The error message ValueError: arrays must all be same length

sns.lineplot( x1, x1.index, ['x25','x50','x75','x100','x125'])

could somebody please let me know, what i am doing wrong.

Answer 1

Consider calling lineplot multiple times, passing in object such as pandas series to named arguments:

sns.lineplot(x=x1.index, y=x1['x25'])
sns.lineplot(x=x1.index, y=x1['x50'])
sns.lineplot(x=x1.index, y=x1['x75'])
sns.lineplot(x=x1.index, y=x1['x100'])
sns.lineplot(x=x1.index, y=x1['x125'])

Or in loop:

for i in  ['x25','x50','x75','x100','x125']:
   sns.lineplot(x=x1.index, y=x1[i])

---

However, consider using a single data frame and hence single lineplot call by melting your wide data to long and rendering your index as a column. Then call lineplot with hue for automatic legend:

# CREATE NEW COLUMN NAMED index
x1 = x1.reset_index()

# MELT DATA
mdf = x1.melt(id_vars='index')

# PLOT LINE WITH data AND hue ARGUMENTS
sns.lineplot(x='index', y='value', data=mdf, hue='variable')

---

Data

df = pd.DataFrame({'X': np.random.uniform(2000, 5000, 500)})

x1 = pd.DataFrame({'x25': df['X'][0:45].reset_index(drop=True),
                   'x50': df['X'][90:135].reset_index(drop=True),
                   'x75': df['X'][180:225].reset_index(drop=True),
                   'x100': df['X'][270:315].reset_index(drop=True),
                   'x125': df['X'][360:405].reset_index(drop=True)})