seaborn pratical machine learing data science

# # seaborn pratical 

# In[19]:

import  matplotlib.pyplot as plt

import seaborn as sns

import pandas as pd

# In[ ]:

# sns.lineplot(

#     x=None,

#     y=None,

#     hue=None,

#     size=None,

#     style=None,

#     data=None,

#     palette=None,

#     hue_order=None,

#     hue_norm=None,

#     sizes=None,

#     size_order=None,

#     size_norm=None,

#     dashes=True,

#     markers=None,

#     style_order=None,

#     units=None,

#     estimator='mean',

#     ci=95,

#     n_boot=1000,

#     seed=None,

#     sort=True,

#     err_style='band',

#     err_kws=None,

#     legend='brief',

#     ax=None,

#     **kwargs,

# )

# In[34]:

days =       [1,2,3,4,5,6,7,8,9,10,11,12,13,14,15]

temperature= [26,52,25,55,26,45,42,5,2,45,42,45,45,9,8]

temp_df=pd.DataFrame({"days":days, "temperature":temperature})

sns.lineplot(x="days",y="temperature",data=temp_df,)

plt.show()

# In[64]:

book1=pd.read_csv("I:\JNPY\mL imp\ML Project 1\Book2.csv")

book1.head()

# In[66]:

sns.lineplot(x="4no",y="total",data=book1)

plt.show()

# In[75]:

hous=pd.read_csv("I:\JNPY\mL imp\ML Project 1\house_price.csv")

hous.head()

# In[79]:

sns.lineplot(x="Sq.ft",y="Price",data=hous)

plt.show()

# # using hue opration

# In[83]:

hous=pd.read_csv("I:\JNPY\mL imp\ML Project 1\house_price.csv")

sns.lineplot(x="Sq.ft",y="Price",data=hous,hue="Location")

plt.show()

# # using style opration

# In[85]:

hous=pd.read_csv("I:\JNPY\mL imp\ML Project 1\house_price.csv")

sns.lineplot(x="Sq.ft",y="Price",data=hous,hue="Location",style="Location")

plt.show()

# # using palette opration

# 

# palette is use to change the color of grah

# In[87]:

hous=pd.read_csv("I:\JNPY\mL imp\ML Project 1\house_price.csv")

sns.lineplot(x="Sq.ft",y="Price",data=hous,hue="Location",style="Location",palette="hot")

plt.show()

# # Using markers opration

# In[88]:

hous=pd.read_csv("I:\JNPY\mL imp\ML Project 1\house_price.csv")

sns.lineplot(x="Sq.ft",y="Price",data=hous,hue="Location",style="Location",palette="hot",markers=["o","^"])

plt.show()

# # using legend='brief' opration

# In[93]:

hous=pd.read_csv("I:\JNPY\mL imp\ML Project 1\house_price.csv")

sns.lineplot(x="Sq.ft",y="Price",data=hous,hue="Location",style="Location",

             palette="hot",markers=["o","^"],legend='brief' )

plt.show()

# In[97]:

hous=pd.read_csv("I:\JNPY\mL imp\ML Project 1\house_price.csv")

sns.lineplot(x="Sq.ft",y="Price",data=hous,hue="Location",style="Location",

             palette="hot",markers=["o","^"],legend=False)

plt.show()

# In[99]:

hous=pd.read_csv("I:\JNPY\mL imp\ML Project 1\house_price.csv")

sns.lineplot(x="Sq.ft",y="Price",data=hous,hue="Location",style="Location",

             palette="hot",markers=["o","^"],legend="full")

plt.show()

# In[106]:

plt.figure(figsize = (25,9))

hous=pd.read_csv("I:\JNPY\mL imp\ML Project 1\house_price.csv")

sns.lineplot(x="Sq.ft",y="Price",data=hous,hue="Location",style="Location",

             palette="hot",markers=["o","^"],legend="full")

sns.set(style="whitegrid") #hite, dark, whitegrid, darkgrid, ticks

plt.show()