Добавить данные в пустой фрейм данных Pandas

Опубликовано: 27 Марта, 2022

Давайте посмотрим, как добавить данные в пустой фрейм данных Pandas.

Creating the Data Frame and assigning the columns to it

# 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)

Выход :

При добавлении значений с плавающей запятой в столбец с типом данных с целым значением типовое преобразование результирующего столбца кадра данных в тип с плавающей запятой для размещения значения с плавающей запятой.

If we use the argument ignore_index = True => that the index values will remain continuous instead of starting again from 0, be default it’s value is False

# 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)  

Выход :

When we appended the boolean format data into the data frame that was already of the type of float columns then it will change the values accordingly in order to accommodate the boolean values in the float data type domain only.

# 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

Выход :

On appending the data of different data types to the previously formed Data Frame then the resultant Data Frame columns type will always be of the wider spectrum data type.

# 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)

Выход :

If we aim to create a data frame through a for loop then the most efficient way of doing that is as follows :

# 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)

Выход

If we attempt to add different column than already in the data frame then results are as follows :

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

Output :

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Добавить данные в пустой фрейм данных Pandas

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