Create DataFrame
What is Data Frame? A Data frame is a 2D (two-dimensional) data structure, i.e., data is arranged in tabular form i.e. In rows and columns.
Or we can say that, Pandas DataFrame is similar to excel sheet Let's understand it through an example
known as Indexes
Name 0 Arprit
Age 62
Department Surgery
Charges Gender
300
M
1 Zarina 22
ENT
250
F
2 Kareem 32
Orthopaedic 200
M
3 Arun
12
Surgery
300
M
4 Zubin 30
ENT
250
M
5 Kettaki 16
ENT
250
F
6 Ankita 29
Cardiology
800
F
7 Zareen 45
300
F
8 Kush 19
Cardiology
800
M
I9d Shilpa 23
Nuclear
400
F
1. Create DMaetdaicFinrae me
Known as Columns
Data Values
pandas DataFrame can be created using the following constructor -
pandas.DataFrame( data, index, columns, dtype, copy)
The parameters of the constructor are as follows -
Sr.No
Parameter & Description
1
Data data takes various forms like ndarray, series, map, lists, dict, constants and
also another DataFrame.
2
Index For the row labels, the Index to be used for the resulting frame is Optional
Default np.arrange(n) if no index is passed.
3
Columns For column labels, the optional default syntax is - np.arrange(n). This is
only true if no index is passed.
4
Dtype Data type of each column.
5
Copy This command (or whatever it is) is used for copying of data, if the default is
False.
pythonclassroomdiary. by Sangeeta M Chauhan , PGT CS KV NO.3 Gwalior
A pandas DataFrame can be created using various inputs like -
Lists
dictionary
Series
Numpy ndarrays
Another DataFrame
1.1 Create an Empty DataFrame
>>> import pandas as pd >>> df=pd.DataFrame() >>> df
Empty DataFrame Columns: [] Index: []
1.2 Create a DataFrame from Lists Example 1
>>> MyList=[10,20,30,40] >>> MyFrame=pd.DataFrame(MyList) >>> MyFrame
0 0 10 1 20 2 30 3 40
Example 2: (Nested List)
>>> Friends = [['Shraddha','Doctor'],['Shanti','Teacher'],['Monica','Engineer']]
>>> MyFrame=pd.DataFrame(Friends,columns=['Name','Occupation']) >>> MyFrame
Name Occupation 0 Shraddha Doctor 1 Shanti Teacher 2 Monica Engineer
1.3 Creation of a DataFrame from Dictionary of ndarrays / Lists
All the ndarrays must be of same length. If index is passed, then the length of the index should equal to the length of the
arrays. If no index is passed, then by default, index will be range(n), where n is the array
length.
pythonclassroomdiary. by Sangeeta M Chauhan , PGT CS KV NO.3 Gwalior
Example 1 (without index)
>>> data = {'Name':['Shraddha', 'Shanti', 'Monica', 'Yogita'],'Age':[28,34,29,39]}
>>> df = pd.DataFrame(data) >>> df
Name Age 0 Shraddha 28 1 Shanti 34 2 Monica 29 3 Yogita 39
Example 2 (with index)
>>> data = {'Name':['Shraddha', 'Shanti', 'Monica',
'Yogita'],'Age':[28,34,29,39]}
>>> df = pd.DataFrame(data, index=['Friend1','Friend2','Relative1','Relative2'])
>>> df
Name Age
Friend1 Shraddha 28
Friend2
Shanti 34
Relative1 Monica 29
Relative2 Yogita 39
1.4 Create a DataFrame from List of Dictionaries
Here we are passing list of dictionary to create a DataFrame. The dictionary
keys are by default taken as column names.
Example 1:
>>> Mydict= [{'Won': 15, 'Loose': 2},{'Won': 5, 'Loose': 10}, {'Won': 8, 'Loose': 9},{'Won':4}]
>>> df = pd.DataFrame(Mydict) >>> df
Loose Won 0 2.0 15 1 10.0 5 2 9.0 8 3 NaN 4
Notice that Missing Value is stored as NaN (Not a Number)
Example 2:
>>> Mydict=[{'Won': 15, 'Loose': 2},{'Won': 5, 'Loose': 10},{'Won': 8, 'Loose':
9}] >>> df = pd.DataFrame(Mydict, index=['India', 'Pakistan','Autralia']) >>> df
Loose Won
India
2 15
Pakistan
10 5
Autralia
9 8
pythonclassroomdiary. by Sangeeta M Chauhan , PGT CS KV NO.3 Gwalior
Example 3 We can also create a DataFrame with by specifying list of dictionaries, row indices, and column indices.
>>> L_dict = [{'Maths': 78, 'Chemistry': 78,'Physics':87},{'Maths': 67, 'Chemistryb': 70},{'Physics':77,'Maths':87}]
A
>>> df1 = pd.DataFrame(L_dict, index=['Student1', 'Student2','Student3'],
columns=['Physics', 'Chemistry','Maths'])
>>> df1
Student1 Student2 Student3
Physics
87.0 NaN
77.0
Chemistry
78.0 NaN NaN
Maths
78 67 87
B
>>> df2 = pd.DataFrame(L_dict, index=['Student1', 'Student2','Student3'],
columns=['Chemistry','Maths'])
>>> df2
Student1 Student2 Student3
Chemistry
78.0 NaN NaN
Maths
78 67 87
>>> df3 = pd.DataFrame(L_dict, index=['Student1', 'Student2','Student3'],
C
columns=['English','Chemistry','Maths'])
>>> df3
Student1 Student2 Student3
English
NaN NaN NaN
Chemistry
78.0 NaN NaN
Maths
78 67 87
Observe the lines mentioned with A, B and C above.Output of A,B,C
are depends upon the COLUMNS MENTIONED while creating DataFrame. If
Dictionary Keys are matched with Columns specified then the
corresponding data will be shown. If columns mentioned are not
matched with Keys then NaN will be displayed
2. Addition of New Column & Row
2.1 Column Addition
>>> L_dict = [{'Maths': 78, 'Chemistry': 78,'Physics':87},{'Maths': 67, 'Chemistry': 70},{'Physics':77,'Maths':87,'Chemistry':90}]
df3 = pd.DataFrame(L_dict, index=['Student1', 'Student2','Student3'], columns=['English','Chemistry','Maths'])
>>> df3['Physics']=[45,56,65]
pythonclassroomdiary. by Sangeeta M Chauhan , PGT CS KV NO.3 Gwalior
>>> df3
A new column' Physics' has been added with new data
Student1 Student2 Student3
English NaN NaN NaN
Chemistry 78 70 90
Maths 78 67 87
Physics 45 56 65
We can Update column Data also by using same method
>>> df3['English']=[78,98,89]
>>> df3
English Chemistry Maths Physics
Student1
78
78
78
45
Student2
98
70
67
56
Student3
89
90
87
65
We can add new column using Data ,stored in existing Frame
>>> df3['Total']=df3.English+df3.Chemistry+df3.Maths+df3.Physics
>>> df3
Student1 Student2 Student3
English 78 98 89
Chemistry 78 70 90
Maths 78 67 87
Physics 45 56 65
Total 279 291 331
2.2 Row Addition
Look a new Column Total has been added with total of marks in other subjects
i.
To add row with by specifying row index
>>> df3.loc['Student4']=[45,67,45]
>>> df3
English Chemistry Maths
Student1
78
Student2
98
78
78
70
67
Student3
89
Student4
45
90
87
67
45
ii.
To add/Modify row with by specifying row index no.
>>> df3.iloc[3]=[45,67,45]
>>> df3
English Chemistry Maths
Student1
78
78
78
Student2
98
70
67
Student3
89
90
87
Student4
45
67
45
>>> df3.iloc[3]=[65,77,90]
>>> df3
Student1 Student2 Student3 Student4
English 78 98 89 65
Chemistry 78 70 90 77
Maths 78 67 87 90
pythonclassroomdiary. by Sangeeta M Chauhan , PGT CS KV NO.3 Gwalior
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