python plotly time series handle missing dates corretly

Question

I am using Python 3.6 in Spyder and try to plot a graph with the plotly offline library. Anyways I have some missing dates in my csv-file and I think they cause the problem you can see in the attached screenshot.

Here is my python code:

from plotly.offline import plot
import plotly.graph_objs as go

import pandas as pd

df = pd.read_csv('H://python/final_mk_output_regression.csv')

data = [go.Scatter(
          x=df.MESS_DATUM,
          y=df['sum_meal'])]

plot(data)

I can not get a correct graph. For example the part before May is very confusing. I have missing dates in my csv-file from 18th April until 30th April which maybe cause this problem. How can I solve this problem?

Your data is messy, or the format with which the mixes read it, for me it is the first case. — eyllanesc, Dec 11 '17 at 08:38
I forgot to mention that I already checked my data with a count. I have no duplicate dates in my file. — adama, Dec 11 '17 at 08:44
'MESS_DATUM' is the date in the x-axis and 'sum_meal' should be the value for the y-axis — adama, Dec 11 '17 at 09:42

score 4 · Answer 1 · answered Mar 29 '18 at 12:01

Simply add type="category" to the code. Here we go:

#PRINT DATA
data = [go.Scatter(
                x=df.MESS_DATUM,
                y=df['sum_meal'])]
layout = dict(
                title="timeline meal orders",
                xaxis = dict(
                type="category"))
fig = dict(data=data, layout=layout)
plot(fig, filename="overview")

score 3 · Answer 2 · answered Apr 15 '20 at 04:12

Only adding type='categry' wouldn't help because it will give unsorted date and time. You will also need to add categoryorder='category ascending'.

Here is the modified code:

data = [go.Scatter(
            x=df.MESS_DATUM,
            y=df['sum_meal'])]

layout = dict(
            title="timeline meal orders",
            xaxis = dict(
            type="category", 
            categoryorder='category ascending'))

fig = dict(data=data, layout=layout)
plot(fig, filename="overview")

python plotly time series handle missing dates corretly

2 Answers2

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