Issue
I have a temperature file with many years temperature records, in a format as below:
2012-04-12,16:13:09,20.6
2012-04-12,17:13:09,20.9
2012-04-12,18:13:09,20.6
2007-05-12,19:13:09,5.4
2007-05-12,20:13:09,20.6
2007-05-12,20:13:09,20.6
2005-08-11,11:13:09,20.6
2005-08-11,11:13:09,17.5
2005-08-13,07:13:09,20.6
2006-04-13,01:13:09,20.6
Every year has different numbers, time of the records, so the pandas datetimeindices are all different.
I want to plot the different year's data in the same figure for comparing . The X-axis is Jan to Dec, the Y-axis is temperature. How should I go about doing this?
Solution
- Chang's answer shows how to plot a different DataFrame on the same
axes
. - In this case, all of the data is in the same dataframe, so it's better to use
groupby
andunstack
.- Alternatively,
pandas.DataFrame.pivot_table
can be used. dfp = df.pivot_table(index='Month', columns='Year', values='value', aggfunc='mean')
- Alternatively,
- When using
pandas.read_csv
,names=
creates column headers when there are none in the file. The'date'
column must be parsed intodatetime64[ns] Dtype
so the.dt
extractor can be used to extract themonth
andyear
.
import pandas as pd
# given the data in a file as shown in the op
df = pd.read_csv('temp.csv', names=['date', 'time', 'value'], parse_dates=['date'])
# create additional month and year columns for convenience
df['Year'] = df.date.dt.year
df['Month'] = df.date.dt.month
# groupby the month a year and aggreate mean on the value column
dfg = df.groupby(['Month', 'Year'])['value'].mean().unstack()
# display(dfg)
Year 2005 2006 2007 2012
Month
4 NaN 20.6 NaN 20.7
5 NaN NaN 15.533333 NaN
8 19.566667 NaN NaN NaN
Now it's easy to plot each year as a separate line. The OP only has one observation for each year, so only a marker is displayed.
ax = dfg.plot(figsize=(9, 7), marker='.', xticks=dfg.index)
Answered By - Andy Hayden
0 comments:
Post a Comment
Note: Only a member of this blog may post a comment.