Plot time series data

[schniefen]

I have a long list of data looking like this:

   

Minute and Second are always zero since the data is the 1 hour average of a measurement, which is the last column. I would like to plot this data. If there was only two columns, date and measurement, then I would simply do:

import pandas as pd
import matplotlib.pyplot as plt
df=pd.read_csv('data.csv')
plt.plot(df)

So I am considering to rewrite the dataframe, however, I am unsure if this approach will work. Appreciate any feedback.

[noisefloor]

Hi,

if you combine the first six columns to one column holding a datetime object, plotting should be easy.

Regards, noisefloor

[schniefen]

Hi,

if you combine the first six columns to one column holding a datetime object, plotting should be easy.

Regards, noisefloor

Here is my current solution, which I'd like to shorten if possible:

import pandas as pd
import matplotlib.pyplot as plt
df=pd.read_csv('data.csv')
df['Date']=pd.to_datetime(df[['Year', 'Month', 'Day', 'Hour', 'Minute','Second']])
df=df.drop(['Year', 'Month', 'Day', 'Hour', 'Minute','Second'], axis=1)
df=df.dropna()
plt.plot(df['Date'],df['HYY_META.VOC_M137_1250'])

[noisefloor]

Hi,

what to you mean by "shorten"? The code is already pretty short... If you like to get rid of one line, you can skip line 5 in your code and skip deleting the year, month, ... columns, as there not a real need for it.

You could also shorten the code if the input csv would have a column for datetime already instead of six columns. In case you have an impact on how the csv file is structured.

Regards, noisefloor