pandas operations

  import pandas as pd

dict={'day':[1,2,3,4,5,6],'visitors':[1000,2000,3000,4000,5000,6000],'bounce_rate':[20,30,40,50,60,70]}
df=pd.DataFrame(dict)
print(df)

#operations on pandas
 #1. slicing of data
   #eg1. printing 1sst two rows of data only
a=df.head(2)
print(a)
#eg2. printing last 2 rows of data
b=df.tail(2)
print(b)

  #2. merging of datasets
  # while merging same table of two different data it will seperate the table individually mendioning x and y
data1={"city":['kathmandu','biratnagar','bhairahawa','pokhara'],"humidity":[1200,1300,1400,1500],"saturation":[1,2,3,4]}
df1=pd.DataFrame(data1)
print(df1)
data2={"city":['kathmandu','biratnagar','bhairahawa','pokhara'],"humidity":[1400,400,200,800],"saturation":[5,6,7,8]}
df2=pd.DataFrame(data2)
print(df2)
df3=pd.merge(df1,df2,on='city')
print(df3)
  # while merging two data missi=ing any table than it will merge those to form one : inner join i,e takes only intersection
data1={"city":['kathmandu','biratnagar','bhairahawa','pokhara'],"humidity":[1200,1300,1400,1500]}
df1=pd.DataFrame(data1)
print(df1)
data2={"city":['kathmandu','biratnagar','bhairahawa','pokhara','birgunj'],"saturation":[5,6,7,8,9]}
df2=pd.DataFrame(data2)
print(df2)
df3=pd.merge(df1,df2,on='city' )
print(df3)
# while merging two data missi=ing any table than it will merge those to form one : left join i,e takes only left table content
data1={"city":['kathmandu','biratnagar','bhairahawa','pokhara'],"humidity":[1200,1300,1400,1500]}
df1=pd.DataFrame(data1)
print(df1)
data2={"city":['kathmandu','biratnagar','bhairahawa','pokhara','birgunj'],"saturation":[5,6,7,8,9]}
df2=pd.DataFrame(data2)
print(df2)
df3=pd.merge(df1,df2,on='city',how='left' )
print(df3)
# while merging two data missi=ing any table than it will merge those to form one : right join i,e takes only right table content
data1={"city":['kathmandu','biratnagar','bhairahawa','pokhara'],"humidity":[1200,1300,1400,1500]}
df1=pd.DataFrame(data1)
print(df1)
data2={"city":['kathmandu','biratnagar','bhairahawa','pokhara','birgunj'],"saturation":[5,6,7,8,9]}
df2=pd.DataFrame(data2)
print(df2)
df3=pd.merge(df1,df2,on='city',how='right' )
print(df3)


#3. changing the index value

data4={"city":['kathmandu','biratnagar','bhairahawa','pokhara'],"humidity":[1200,1300,1400,1500]}
df4=pd.DataFrame(data4)
df4.set_index(['city'],inplace=True)
print(df4)

#4. changing column name

data5={"city":['kathmandu','biratnagar','bhairahawa','pokhara'],"humidity":[1200,1300,1400,1500]}
df5=pd.DataFrame(data5)
df5=df5.rename(columns={"city":"state"})
print(df5)