Timeline charts, heat maps
tsplot() / heatmap()

1. Timeline chart-tsplot ()

Example 1:

import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
import seaborn as sns

 #Set style, scale
sns.set_style('darkgrid')
sns.set_context('paper')

 #No warning
import warnings
warnings.filterwarnings('ignore')

x = np.linspace(0, 15, 31)
data = np.sin(x) + np.random.rand(10,31) + np.random.randn(10,1)
print(data.shape)
print(pd.DataFrame(data).head())

sns.tsplot(data = data,
                       err_style = 'ci_band', #Error data style, optional: ci_band, ci_bars, boot_traces,
           #boot_kde, unit_traces, unit_points
                       interpolate = True, #Set connection
                       ci = [40, 70, 90], #set error interval
                       color = 'g' #Set the color
           )

Example 2:

sns.tsplot(data = data, err_style = 'boot_traces',
                       n_boot = 300 #number of iterations
           )

Example 3:

#parameter settings 
 #Import Data 
gammas = sns.load_dataset('gammas')
print(gammas.head())
 print ('The amount of data is:% i'% len (gammas))
 print (The amount of data when 'timepoint is 0.0 is:% i  '% len (gammas [gammas ['timepoint'] == 0]))
 #View only specific information
 print ('timepoint has% i unique values'% len (gammas ['timepoint']. value_counts ()))

 sns.tsplot (time = 'timepoint', #time data, x-axis
                       value = 'BOLD signal', #yaxis value
                       unit = 'subject', #split, default parameter
                       condition = 'ROI', #classification
           data = gammas
           )

2. Heatmap-heatmap ()

Example 1:

df = pd.DataFrame(np.random.rand(10,12))
 sns.heatmap (df, #load data
                         vmin = 0, vmax = 1 #Set the maximum and minimum values ​​of the legend
            )

Example 2: Setting parameters

#Setting parameters 
 #Download Data 
flights = sns.load_dataset('flights')
flights = flights.pivot('month','year','passengers')
print(flights.head())

sns.heatmap(flights,
                         annot = True, #Whether to display the value
                         fmt = 'd', #format string
                         linewidth = 0, #Grid side line width
                         center = 100, #The color center value of the color palette, if not specified, cmap is the main
                         cmap = 'Reds', #set palette
                         cbar = True, # Whether to display the legend ribbon
                         #bar_kws = ['orientaion': 'horizaintal'], #Whether to display the legend ribbon horizontally
                         #square = True #Whether the square displays the chart
            )

Example 3: Drawing a half-edge heat map

#Set style
sns.set(style = 'white')
 #Create data
rs = np.random.RandomState(33)
d = pd.DataFrame(rs.normal(size = (100, 26)))
 corr = d.corr () #Solve the correlation matrix table
 #Set an ‘upper triangle’ mask
mask = np.zeros_like(corr, dtype = np.bool)
mask[np.triu_indices_from(mask)] = True
 #Set the palette
cmap = sns.diverging_palette(220, 10, as_cmap = True)
 #Generate half-edge heatmap
sns.heatmap(corr, mask = mask, cmap = cmap, vmax = .3, center = 0,
            square = True, linewidths = 0.2)