Pandas DataFrame.to_dict() Function
Python Pandas DataFrame.to_dict() function converts the given DataFrame to a dictionary.
pandas.DataFrame.to_dict()
Syntax
DataFrame.to_dict(orient='dict',
into= < class 'dict' >)
parameter
orient |
This parameter determines the type of the dictionary. For example, it can be a dictionary of series or lists. It has six options. They are dict , list , series , split , records and index . |
into |
It is a class parameter. We can pass an actual class or its instance as a parameter. |
return
It returns a dictionary representing the passed Dataframe.
Example Code: DataFrame.to_dict()
Method to Convert DataFrame to Dictionary of Dictionaries
To convert the DataFrame to a dictionary of dictionaries, we will not pass any arguments.
import pandas as pd
dataframe=pd.DataFrame({'Attendance': {0: 60, 1: 100, 2: 80,3: 78,4: 95},
'Name': {0: 'Olivia', 1: 'John', 2: 'Laura',3: 'Ben',4: 'Kevin'},
'Obtained Marks': {0: 90, 1: 75, 2: 82, 3: 64, 4: 45}})
print("The Original Data frame is: \n")
print(dataframe)
dataframe1 = dataframe.to_dict()
print("The Dictionary of Dictionaries is: \n")
print(dataframe1)
Output:
The Original Data frame is:
Attendance Name Obtained Marks
0 60 Olivia 90
1 100 John 75
2 80 Laura 82
3 78 Ben 64
4 95 Kevin 45
The Dictionary of Dictionaries is:
{'Attendance': {0: 60, 1: 100, 2: 80, 3: 78, 4: 95}, 'Obtained Marks': {0: 90, 1: 75, 2: 82, 3: 64, 4: 45}, 'Name': {0: 'Olivia', 1: 'John', 2: 'Laura', 3: 'Ben', 4: 'Kevin'}}
This function returns a dictionary of dictionaries.
Example Code: How to DataFrame.to_dict()
Convert DataFrame to Series
Dictionary
To convert a DataFrame to Series
a dictionary of , we pass series
as orient
the argument.
import pandas as pd
dataframe=pd.DataFrame({'Attendance': {0: 60, 1: 100, 2: 80,3: 78,4: 95},
'Name': {0: 'Olivia', 1: 'John', 2: 'Laura',3: 'Ben',4: 'Kevin'},
'Obtained Marks': {0: 90, 1: 75, 2: 82, 3: 64, 4: 45}})
print("The Original Data frame is: \n")
print(dataframe)
dataframe1 = dataframe.to_dict('series')
print("The Dictionary of Series is: \n")
print(dataframe1)
Output:
The Original Data frame is:
Attendance Name Obtained Marks
0 60 Olivia 90
1 100 John 75
2 80 Laura 82
3 78 Ben 64
4 95 Kevin 45
The Dictionary of Series is:
{'Attendance': 0 60
1 100
2 80
3 78
4 95
Name: Attendance, dtype: int64, 'Obtained Marks': 0 90
1 75
2 82
3 64
4 45
Name: Obtained Marks, dtype: int64, 'Name': 0 Olivia
1 John
2 Laura
3 Ben
4 Kevin
Name: Name, dtype: object}
The function returns Series
a dictionary.
For reprinting, please send an email to 1244347461@qq.com for approval. After obtaining the author's consent, kindly include the source as a link.
Related Articles
Pandas DataFrame.astype() Function
Publish Date:2025/05/01 Views:160 Category:Python
-
Python Pandas DataFrame.astype() function changes the data type of an object to the specified data type. pandas.DataFrame.astype() grammar DataFrame . astype(dtype, copy = True , errors = "raise" ) parameter dtype The data type we want to a
Pandas DataFrame.reset_index() Function
Publish Date:2025/05/01 Views:140 Category:Python
-
Python Pandas DataFrame.reset_index() function resets the index of the given DataFrame. It replaces the old index with the default index. If the given DataFrame has a MultiIndex, then this method removes all the levels. pandas.DataFrame.rep
Pandas DataFrame.resample() Function
Publish Date:2025/05/01 Views:78 Category:Python
-
Python Pandas DataFrame.resample() function resamples time series data. pandas.DataFrame.resample() Syntax DataFrame . resample( rule, axis = 0 , closed = None , label = None , convention = "start" , kind = None , loffset = None , base = No
Pandas DataFrame.insert() Function
Publish Date:2025/05/01 Views:116 Category:Python
-
Python Pandas DataFrame.insert() function inserts a column at the specified position into the DataFrame. pandas.DataFrame.insert() Syntax DataFrame . insert(loc, column, value, allow_duplicates = False ) parameter loc It is an integer param
Pandas DataFrame.idxmax() Function
Publish Date:2025/05/01 Views:79 Category:Python
-
Python Pandas DataFrame.idxmax() function returns the index of the maximum value in a row or column. pandas.DataFrame.idxmax() Syntax DataFrame . idxmax(axis = 0 , skipna = True ) parameter axis It is a parameter of integer or string type.
Pandas DataFrame sort_index() Function
Publish Date:2025/05/01 Views:183 Category:Python
-
This tutorial explains how to use pandas.DataFrame.sort_index() the sort method to sort a Pandas DataFrame based on its index. We will use the DataFrame shown in the above example to explain how to sort a Pandas DataFrame based on the index
Pandas cut function
Publish Date:2025/05/01 Views:165 Category:Python
-
pandas.cut() The function can distribute the given data into a range, which can also be called bins . We will use the following DataFrame in this article. import pandas as pd df = pd . DataFrame( { "Name" : [ "Anish" , "Birat" , "Chirag" ,
Appending to an Empty DataFrame in Pandas
Publish Date:2025/05/01 Views:54 Category:Python
-
As we learned earlier, Pandas in Python is an open source module that we can use for data analysis and making machine learning models. It is Numpy used along with another package called as they go hand in hand to support multidimensional ar
Pandas DataFrame DataFrame.query() function
Publish Date:2025/04/30 Views:108 Category:Python
-
The pandas.DataFrame.query() method filters the rows of the caller DataFrame using the given query expression. pandas.DataFrame.query() grammar DataFrame . query(expr, inplace = False , ** kwargs) parameter expr Filter rows based on query e