In [21]:

import pandas as pd
import matplotlib.pyplot as plt
from matplotlib import style
style.use("fivethirtyeight")

dictionary = {"Rank": [3, 2, 4, 5, 6], "Name": ["Tanu", "Ashika", "Ashwin", "Mohit", "Sourabh"], "Age": [23, 24, 22, 18, 9], "Weight": [69, 72, 65, 70, 40], "Occupation": ["Student", "Working", "Working", "Student", "Student"]}
df = pd.DataFrame(dictionary)

# Slicing the dataframe
df.head(3)

Out[21]:

	Rank	Name	Age	Weight	Occupation
0	3	Tanu	23	69	Student
1	2	Ashika	24	72	Working
2	4	Ashwin	22	65	Working

In [22]:

df.tail(1)

Out[22]:

	Rank	Name	Age	Weight	Occupation
4	6	Sourabh	9	40	Student

In [23]:

dictionary1 = {"Rank": [1], "Name": ["Tilo"], "Age": [80], "Weight": [80], "Occupation": ["Kitchen Queen"] }
df1 = pd.DataFrame(dictionary1)
# Concatenating the two dataframes (df, df1)
df_row = pd.concat([df, df1])
df_row

Out[23]:

	Rank	Name	Age	Weight	Occupation
0	3	Tanu	23	69	Student
1	2	Ashika	24	72	Working
2	4	Ashwin	22	65	Working
3	5	Mohit	18	70	Student
4	6	Sourabh	9	40	Student
0	1	Tilo	80	80	Kitchen Queen

In [24]:

# To set the first as Rank
df_row.set_index("Rank", inplace = True)

# To sort the data Rank in the ascending order
df_row.sort_values(by=['Rank'])

Out[24]:

	Name	Age	Weight	Occupation
Rank
1	Tilo	80	80	Kitchen Queen
2	Ashika	24	72	Working
3	Tanu	23	69	Student
4	Ashwin	22	65	Working
5	Mohit	18	70	Student
6	Sourabh	9	40	Student

In [25]:

df_row.plot()
plt.show()

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