# importing the module
import pandas as pd
  
# creating the DataFrame of int and float
a = [[1, 1.2], [2, 1.4], [3, 1.5], [4, 1.8]]
t = pd.DataFrame(a, columns =["A", "B"])
  
# displaying the DataFrame
print(t)
print(t.dtypes)

# Appending a Data Frame of float and int
s = pd.DataFrame([[1.3, 9]], columns = ["A", "B"])
display(s)
  
# makes index continuous
t = t.append(s, ignore_index = True)  
display(t)
  
# Resultant data frame is of type float and float
display(t.dtypes)  

# Appending a Data Frame of bool and bool
u = pd.DataFrame([[True, False]], columns =["A", "B"])
display(u)
display(u.dtypes)
  
t = t.append(u)
display(t)
display(t.dtypes)  # type casted into float and float

# Appending a Data Frame of object and object
x = pd.DataFrame([["1.3", "9.2"]], columns = ["A", "B"])
display(x)
display(x.dtypes)
  
t = t.append(x)
display(t)
display(t.dtypes)

# Creating a DataFrame using a for loop in efficient manner
y = pd.concat([pd.DataFrame([[i, i * 10]], columns = ["A", "B"])
               for i in range(7, 10)], ignore_index = True)
  
# makes index continuous
t = t.append(y, ignore_index = True)  
display(t)
display(t.dtypes)

# Appending Different Columns
z = pd.DataFrame([["1.3", "9.2"]], columns = ["E", "F"])
t = t.append(z)
print(t)
print(t.dtypes)
print()