Incorrect plot being displayed using pandas

Question

I am doing a time series analysis:

interval_data_file.csv is a csv file, with two columns: Time and Freq.

import pandas as pd
import datetime
import numpy as np
import matplotlib.pylab as plt
from matplotlib.pylab import rcParams

rcParams['figure.figsize'] = 300, 20

DATETIME_FORMAT = "%Y-%m-%d %H:%M:%S"
INPUT_FILE = 'interval_data_file.csv'


dateparse = lambda dates: pd.datetime.strptime(dates, DATETIME_FORMAT)
data = pd.read_csv(INPUT_FILE, parse_dates=True, index_col='Time',
                   date_parser=dateparse)


print data.index

ts = data['Freq']
#print ts.head(10)

print ts['1970-02-04 20:12:16']

plt.plot(ts)
plt.show()

This is the plot outputted which is obviously wrong:

Can someone suggest what I am doing wrong?

Why do you think the output plot is wrong? Looking at your data, it seems pretty correct. — ImportanceOfBeingErnest
– ImportanceOfBeingErnest, Commented Dec 17, 2016 at 13:55
Since you already have frequency counts, did you give bar plot a try which seems ideal for such a purpose and see if you get the right results? You need to do - plt.bar(ts.index, ts) if you intend on doing via matplotlib. — Nickil Maveli
– Nickil Maveli, Commented Dec 17, 2016 at 13:56

Marc vT · Accepted Answer · 2016-12-17 14:01:29Z

2

I think the issue is that you are not sorting your index. Try:

data.sort_index(inplace=True)

answered Dec 17, 2016 at 14:01

Marc vT

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