« Pandas
Pandas.DataFrame is the two dimensional array
import pandas as pd
my_dict={
'NAME':['Ravi','Raju','Alex'],
'ID':[1,2,3],'MATH':[30,40,50],
'ENGLISH':[20,30,40]
}
my_data = pd.DataFrame(data=my_dict)
print(my_data)
Output is here
NAME ID MATH ENGLISH
0 Ravi 1 30 20
1 Raju 2 40 30
2 Alex 3 50 40
Here we used one Dictionary to create one DataFrame. We can also use Numpy Ndarray to create DataFrame.
Adding index
Instead of using built-in index 0,1,3 ( above code ) , we can use our own index.
import pandas as pd
my_dict={'NAME':['Ravi','Raju','Alex'],
'ID':[1,2,3],'MATH':[30,40,50],'ENGLISH':[20,30,40]}
my_data = pd.DataFrame(data=my_dict)
my_data.index=[1,2,3]
print(my_data)
Output is here
NAME ID MATH ENGLISH
1 Ravi 1 30 20
2 Raju 2 40 30
3 Alex 3 50 40
We can use string as index
my_data.index=['a','b','c']
Output is here
NAME ID MATH ENGLISH
a Ravi 1 30 20
b Raju 2 40 30
c Alex 3 50 40
Adding index to columns using set_index()→
Datframe Columns
cols=my_data.columns # list with column names
print(cols)
print(cols[2]) # specific column name
for i in cols: # listing all columns
print(i)
Displaying specific column values
We used list as column names.
import pandas as pd
my_dict={'NAME':['Ravi','Raju','Alex'],
'ID':[1,2,3],'MATH':[30,40,50],'ENGLISH':[20,30,40]}
my_data = pd.DataFrame(data=my_dict)
print(my_data[['NAME','ID']])
Output
NAME ID
0 Ravi 1
1 Raju 2
2 Alex 3
As we used List as column names , we can use all the columns and then remove columns which we don't want to display.
import pandas as pd
my_dict={'NAME':['Ravi','Raju','Alex'],
'ID':[1,2,3],'MATH':[30,40,50],'ENGLISH':[20,30,40]}
my_data = pd.DataFrame(data=my_dict)
my_col_list=list(my_data) # list of column names
my_col_list.remove('ID') # Remove ID from the list of column names
print(my_data[my_col_list])
Output is here
NAME MATH ENGLISH
0 Ravi 30 20
1 Raju 40 30
2 Alex 50 40
More about columns and adding columns to DataFrame→
Specific rows
import pandas as pd
my_dict={'NAME':['Ravi','Raju','Alex'],
'ID':[1,2,3],'MATH':[30,40,50],'ENGLISH':[20,30,40]}
my_data = pd.DataFrame(data=my_dict)
print(my_data[0:2])
Output
NAME ID MATH ENGLISH
0 Ravi 1 30 20
1 Raju 2 40 30
Some more examples
print(my_data[:0])
Output
Empty DataFrame
Columns: [NAME, ID, MATH, ENGLISH]
Index: []
First row
print(my_data[:1])
Output
NAME ID MATH ENGLISH
0 Ravi 1 30 20
Total number of rows
import pandas as pd
my_dict={'NAME':['Ravi','Raju','Alex','Ron','King','Jack'],
'ID':[1,2,3,4,5,6],'MATH':[30,40,50,60,70,80],'ENGLISH':[20,30,40,50,60,70]}
my_data = pd.DataFrame(data=my_dict)
print(len(my_data.index))
Output
6
Creating DataFrame from String
We will use split() to create a list first. Then using the list we will create a DataFrame.
import pandas as pd
str1='Welcome to plus2net python section'
my_list=str1.split(' ')
#print(my_list)
df=pd.DataFrame(data=my_list,columns=['words'])
print(df)
Output is here
words
0 Welcome
1 to
2 plus2net
3 python
4 section
Using StringIO
from io import StringIO
import pandas as pd
str1 = StringIO("""col1;col2;col3
1;5.4;Geek
2;43.25;Ravi
3;41.7;Ron
4;34.2;Alex
""")
df = pd.read_csv(str1, sep=";")
print(df)
Output
col1 col2 col3
0 1 5.40 Geek
1 2 43.25 Ravi
2 3 41.70 Ron
3 4 34.20 Alex
DataFrame Atributes » DataFrame Methods »
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Plotting graphs
Filtering of Data Sample student DataFrame
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