CoCalc -- Visualizations matplotlib pandas.ipynb

GitHub Repository: suyashi29/python-su
Path: blob/master/Data Analysis using Python/Visualizations matplotlib pandas.ipynb
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Kernel: Python 3

In [1]:

import pandas as pd
import seaborn as sns
import numpy as np
import matplotlib.pyplot as plt
from matplotlib.pyplot import pie, axis, show
%matplotlib inline                                                              

import warnings                                                                 # Ignore warning related to pandas_profiling
warnings.filterwarnings('ignore')

In [2]:

viz_data=pd.read_excel("F:\ML & Data Visualization\EXAM PERFORMANCE.xlsx")

In [3]:

viz_data.head(2)

Out[3]:

In [4]:

viz_data["age"].unique()

Out[4]:

array([15, 16, 17], dtype=int64)

In [5]:

viz_data.count()

Out[5]:

Gender             141
age                141
Class              141
math score         141
physics score      141
English            141
chemistry score    141
ROLL NO            141
dtype: int64

In [6]:

viz_data.describe()

Out[6]:

In [7]:

pd.isnull('viz_data')

Out[7]:

False

In [8]:

viz_data['physics score'].plot.hist(orientation='vertical', cumulative=True)

Out[8]:

<matplotlib.axes._subplots.AxesSubplot at 0x247dccd8400>

In [9]:

 ## Histogram
viz_data.plot.hist(stacked=True, bins=20)

Out[9]:

<matplotlib.axes._subplots.AxesSubplot at 0x247dcfef2b0>

In [10]:

 viz_data.plot.hist(stacked=False, bins=20)

Out[10]:

<matplotlib.axes._subplots.AxesSubplot at 0x247dd18a160>

In [11]:

viz_data.plot.hist(color='g', alpha=1, bins=50)##aplha for changing tranparency

Out[11]:

<matplotlib.axes._subplots.AxesSubplot at 0x247dd293400>

In [12]:

viz_data.plot.area()

Out[12]:

<matplotlib.axes._subplots.AxesSubplot at 0x247de5a64e0>

In [13]:

viz_data.plot(kind="bar",x='age',y='math score')

Out[13]:

<matplotlib.axes._subplots.AxesSubplot at 0x247dd16ed68>

In [14]:

viz_data.plot(kind="pie",x='age',y='physics score')

Out[14]:

<matplotlib.axes._subplots.AxesSubplot at 0x247de9b14e0>

In [15]:

viz_data['physics score'].plot.bar(orientation='horizontal')

Out[15]:

<matplotlib.axes._subplots.AxesSubplot at 0x247dea05860>

In [47]:

## boxplot = viz_data.boxplot(by='ROLL NO')
boxplot = viz_data.boxplot(column = ['math score', 'physics score'],   by=['age'])

Out[47]:

In [17]:

import matplotlib.pyplot as plt

fig = plt.figure()
fig.suptitle('Adding Subtitiles', fontsize=14, fontweight='bold')

ax = fig.add_subplot(111)
fig.subplots_adjust(top=0.85)
ax.set_title('axes title')

ax.set_xlabel('Label1')
ax.set_ylabel('Label2')

ax.text(3, 8, 'boxed italics text in data coords', style='italic',
        bbox={'facecolor':'Pink', 'alpha':0.5, 'pad':10})

ax.text(2, 6, r'an equation: $E=mc^2$', fontsize=15)

ax.text(3, 2, u'unicode: Institut f\374r Festk\366rperphysik')

ax.text(0.95, 0.01, 'colored text in axes coords',
        verticalalignment='bottom', horizontalalignment='right',
        transform=ax.transAxes,
        color='green', fontsize=15)


ax.plot([2], [1], 'o')
ax.annotate('annotate', xy=(2, 1), xytext=(3, 4),
            arrowprops=dict(facecolor='black', shrink=0.05))

ax.axis([0, 10, 0, 10])

plt.show()

Out[17]:

In [19]:

rng = np.arange(50)
rnd = np.random.randint(0, 10, size=(3, rng.size))
yrs = 1950 + rng

fig, ax = plt.subplots(figsize=(5, 3))
ax.stackplot(yrs, rng + rnd, labels=['ROSA', 'EPIC', 'MEDAL'])
ax.set_title('Combined debt growth over time')
ax.legend(loc='upper left')
ax.set_ylabel('Total debt')
ax.set_xlim(xmin=yrs[0], xmax=yrs[-1])
fig.tight_layout()

Out[19]:

In [21]:

x = np.random.randint(low=1, high=11, size=50)
y = x + np.random.randint(1, 5, size=x.size)
data = np.column_stack((x, y))
fig, (ax1, ax2) = plt.subplots(nrows=1, ncols=2,
figsize=(8, 4))

ax1.scatter(x=x, y=y, marker='o', c='r', edgecolor='b')
ax1.set_title('Scatter: $x$ versus $y$')
ax1.set_xlabel('X-AXIS')
ax1.set_ylabel('Y-AXIS')

ax2.hist(data, bins=np.arange(data.min(), data.max()),
label=('x', 'y'))
ax2.legend(loc=(0.65, 0.8))
ax2.set_title('Frequencies of $x$ and $y$')
ax2.yaxis.tick_right()

Out[21]:

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