example for this question

example.py

#%%
import os
os.chdir(os.getcwd())

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

from datetime import datetime, timedelta

from pandas.plotting import register_matplotlib_converters
register_matplotlib_converters()


#%%
dfs = pd.read_excel("Daily.xlsx", sheet_name = "Behnam")
dfs.drop(["Medication", "Sleep", "Note"], axis=1, inplace = True)
dfs.dropna(axis = 0, how ='any',  inplace = True)
dfs['Date'] = pd.to_datetime(dfs['Date'], format = '%d-%m-%y')





#%%
dfs = dfs.melt('Date', var_name = 'cols', value_name = 'vals')
# ax = sns.lineplot(x = dfs.index, y = 'Mood', data = dfs)
ax = sns.lineplot(x = "Date", y = 'vals', hue = 'cols', style = 'cols', markers = True, dashes = False, data = dfs)
# ax = sns.factorplot(x = "Date", y = 'vals', hue = 'cols', data = dfs)
ax.set_xticklabels(dfs['Date'].dt.strftime('%d-%m-%Y'))
plt.xticks(rotation = -90)
plt.tight_layout()
plt.show()


#%%

table.txt

+-------+------------+-----+------+------+------+------+-----+
| Index |    Date    | AA  |  BB  |  CC  |  DD  |  EE  | FF  |
+-------+------------+-----+------+------+------+------+-----+
|     0 | 2019-01-15 | 0.0 | -1.0 |  0.0 |  0.0 |  0.0 | 2.0 |
|     1 | 2019-01-17 | 0.0 | -1.0 | -1.0 | -1.0 |  0.0 | 2.0 |
|     2 | 2019-01-22 | 1.0 | -1.0 |  1.0 | -1.0 |  0.0 | 2.0 |
|     3 | 2019-01-24 | 0.0 |  0.0 |  0.0 |  0.0 |  0.0 | 2.0 |
|     4 | 2019-01-29 | 1.0 |  0.0 | -1.0 |  0.0 | -1.0 | 2.0 |
|     5 | 2019-01-31 | 0.0 | -1.0 |  0.0 |  0.0 |  0.0 | 2.0 |
|     6 | 2019-02-05 | 1.0 |  1.0 |  1.0 |  0.0 |  1.0 | 2.0 |
|     7 | 2019-02-12 | 2.0 |  1.0 |  1.0 |  0.0 |  2.0 | 2.0 |
+-------+------------+-----+------+------+------+------+-----+