An exercise in visualization (plotting line plot and multicolored histogram with -ve and +ve values)

This post is an exercise in visualization (plotting line plot and multicolored histogram with -ve and +ve values). We will be using Pandas and Matplotlib libraries.

We are going to do plotting for a week of Nifty50 data from Aug 2017.

import pandas as pd

import matplotlib.pyplot as plt
import matplotlib.dates as mdates
%matplotlib inline

from dateutil import parser

df = pd.read_csv("files_1/201708.csv", encoding='utf8')
df['Change'] = 0
prev_close = 10114.65

def gen_change(row):
    global prev_close
    if row.Date == '01-Aug-2017':
        rtn_val = 0
    else:
        rtn_val = round(((row.Close - prev_close) / prev_close) * 100, 2)
        prev_close = row.Close
    return rtn_val

df.Change = df.apply(gen_change, axis = 1) 

We will plot for only a few dates of Aug 2017:

Line plot: 
subset_df = df[6:13]
plt.figure()
ax = subset_df[['Date', 'Close']].plot(figsize=(20,7))
ax.set_xticks(subset_df.index)
ax.set_ylim([9675, 9950])
ticklabels = plt.xticks(rotation=90)
plt.ylabel('Close')
plt.show() 




Multicolored Histogram for Negative and Positive values

negative_data = [x if x < 0 else 0 for x in list(subset_df.Change.values)]
positive_data = [x if x > 0 else 0 for x in list(subset_df.Change.values)]

fig = plt.figure()
ax = plt.subplot(111)
ax.bar(subset_df.Date.values, negative_data, width=1, color='r')
ax.bar(subset_df.Date.values, positive_data, width=1, color='g')
ticklabels = plt.xticks(rotation=90)
plt.xlabel('Date')
plt.ylabel('% Change')
plt.show()




Link to data file: Google Drive