Shubham Singh shubham-singh-ss

## graph1.py
import matplotlib.pyplot as plt
%matplotlib inline
plt.figure(figsize=(12,8))
nx.draw_networkx(df, with_labels=True)

## graph.py
import networkx as nx
df = nx.from_pandas_edgelist(data, source='Origin', target='Dest', edge_attr=True)
df.nodes()
df.edges()

## datahead.py
data.head()

## importing_the_dataset.py
import pandas as pd
import numpy as np
data = pd.read_csv("data.csv")

## ridgeplot.py
# Initialize the FacetGrid object
g = sns.FacetGrid(df2, row="gender", hue="gender", aspect=5, height=3)

# # Draw the densities in a few steps
g.map(sns.kdeplot, "age", shade=True, alpha=1, lw=3.5, bw=.2)
g.map(sns.kdeplot, "age", color="w", lw=2, bw=.2)
g.map(plt.axhline, y=0, lw=2)

# # Define and use a simple function to label the plot in axes coordinates
def label(x, color, label):

## boxenplot.py
sns.catplot(x="age", y="avg_training_score", data=df2, kind="boxen",height=4, aspect=2.7, hue = "is_promoted")

## heatmap.py
corrmat = df2.corr()
f, ax = plt.subplots(figsize=(9, 6))
sns.heatmap(corrmat, vmax=.8, square=True)

## kdeplot.py
sns.jointplot(x="age", y="avg_training_score", data=df2, kind="kde");

## hexplot.py
sns.jointplot(x=df2.age, y=df2.avg_training_score, kind="hex", data = df2)

## pairplot.py
sns.pairplot(df2)
	import matplotlib.pyplot as plt
	%matplotlib inline
	plt.figure(figsize=(12,8))
	nx.draw_networkx(df, with_labels=True)
	import networkx as nx
	df = nx.from_pandas_edgelist(data, source='Origin', target='Dest', edge_attr=True)
	df.nodes()
	df.edges()
	import pandas as pd
	import numpy as np
	data = pd.read_csv("data.csv")
	# Initialize the FacetGrid object
	g = sns.FacetGrid(df2, row="gender", hue="gender", aspect=5, height=3)

	# # Draw the densities in a few steps
	g.map(sns.kdeplot, "age", shade=True, alpha=1, lw=3.5, bw=.2)
	g.map(sns.kdeplot, "age", color="w", lw=2, bw=.2)
	g.map(plt.axhline, y=0, lw=2)

	# # Define and use a simple function to label the plot in axes coordinates
	def label(x, color, label):
	corrmat = df2.corr()
	f, ax = plt.subplots(figsize=(9, 6))
	sns.heatmap(corrmat, vmax=.8, square=True)