Python-Pandas/dataframe_1creation.py at main · Dhruv-kundu/Python-Pandas · GitHub

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# Dataframe => 2-D => Heterogenous data
# data/ values => mutable

import pandas

# Empty dataframe
df = pandas.DataFrame() # in  DataFrame D,F==> Captial
print(df)
# output
# Empty DataFrame
# Columns: []
# Index: []


# 1==> lists 2==>series  3==> dictionary 4==>NumPy ndarray
# syntax :- pandas.DataFrame(data ,index , columns)
idx=["vijaya" , "rahul" , "meghna" , "radhika" , "shaurya"]
col=["marks", "age" ]
data =[[80,32],[92,28],[67,30],[95,25],[97,20]]
df1=pandas.DataFrame(data ,index= idx ,columns=col)
print(df1)
# output
#          marks  age
# vijaya      80   32
# rahul       92   28
# meghna      67   30
# radhika     95   25
# shaurya     97   20
list=[10,20,30,40,50]
df2=pandas.DataFrame(list)
print(df2)
# output
#     0  <== column label
# 0  10
# 1  20
# 2  30
# 3  40
# 4  50
# |==> index values generated automatically

# Dictionary of series
series1=pandas.Series([1,2,3,4,5])
series2=pandas.Series([10,20,30,40,50])
df3=pandas.DataFrame(data = {
    "ser1":series1  , "ser2":series2
})
print(df3)

# dictionary of list
df4=pandas.DataFrame({"name":["vijaya" , "rahul" , "meghna" , "radhika" , "shaurya"],
"english":[67,78,75,88,92],
"math":[78,67,75,88,92],
"ip":[78,88,98,90,56]} , index =['A','B','C','D','E'])
print(df4)

# LISTS OF DICTIONARY
df5=pandas.DataFrame([{"name":"vijaya", "english ":67 , "math":78 , "ip":78},
{"name":"rahul", "english ":78 , "math":67 , "ip":88},
{"name":"meghna", "english ":75 , "math":75 , "ip":98},
{"name":"radhika", "english ":88 , "math":88 , "ip":90},
{"name":"shaurya", "english ":92 , "math":92 , "ip":56}],index =['A','B','C','D','E'])
print(df5)

# Numpy ndarray
import numpy as np
import pandas as pd

arr1 = np.array(["vijaya", "rahul", "meghna", "radhika", "shaurya"])
arr2 = np.array([67, 78, 75, 88, 92])
arr3 = np.array([78, 67, 75, 88, 92])
arr4 = np.array([78, 88, 98, 90, 56])

df6 = pd.DataFrame({
    "name": arr1,
    "english": arr2,
    "math": arr3,
    "ip": arr4
})

print(df6)