Pandas Plotting PivotTable

Question

I mainly try to reproduce climate charts showing the average temperature and the amount of precipitation during the year for different places.

I created a pivot table from my csv as follows:

data = pd.read_csv("05_temp_rain_v2.csv")
pivot = data.pivot_table(["rain(mm)","temp(dC)"], ["loc","month"])  

Examples of data in text form:

loc,lat,long,year,month,rain(mm),temp(dC)
Adria_-_Bellombra,45.011129,12.034126,1994,1,45.6,4.6  
Adria_-_Bellombra,45.011129,12.034126,1994,2,31.4,4  
Adria_-_Bellombra,45.011129,12.034126,1994,3,1.6,10.7  
Adria_-_Bellombra,45.011129,12.034126,1994,4,74.4,11.5  
Adria_-_Bellombra,45.011129,12.034126,1994,5,26,17.2  
Adria_-_Bellombra,45.011129,12.034126,1994,6,108.6,20.6

Turn table:

As I process various locations, I repeat them:

locations=pivot.index.get_level_values(0).unique()

for location in locations:
    split=pivot.xs(location)

    rain=split["rain(mm)"]
    temp=split["temp(dC)"]

    plt.subplots()
    temp.plot(kind="line",color="r",).legend()
    rain.plot(kind="bar").legend()

An example of graph output is shown below:

Why are my temperature values ​​built since February (2)?
I assume this is due to the fact that the temperature values ​​are indicated in the second column.

What will be the correct way to process and build different data (two columns) from the pivot table?

Answer 1

, line bar xlim . X , . , xlim xticks .

:

In [4]: temp.plot(kind="line",color="r",)
Out[4]: <matplotlib.axes._subplots.AxesSubplot at 0x117f555d0>
In [5]: plt.xticks()
Out[5]: (array([ 1.,  2.,  3.,  4.,  5.,  6.]), <a list of 6 Text xticklabel objects>)

- 1 6.

In [6]: rain.plot(kind="bar").legend()
Out[6]: <matplotlib.legend.Legend at 0x11c15e950>
In [7]: plt.xticks()
Out[7]: (array([0, 1, 2, 3, 4, 5]), <a list of 6 Text xticklabel objects>)

- int 0 5.

, :

temp.plot(kind="line", color="r",).legend()
rain.plot(kind="bar").legend()

:

rain.plot(kind="bar").legend()
plt.plot(range(len(temp)), temp, "r", label=temp.name)
plt.legend()

Answer 2

groupby:

for name, group in data[['loc', 'month', 'rain(mm)', 'temp(dC)']].groupby('loc'):
    group.set_index('month').plot()

Answer 3

jeanrjc answer , , , !

for location in locations:
#print(pivot.xs(location, level=0))

split=pivot.xs(location)
rain=split["rain(mm)"]
temp=split["temp(dC)"]

fig = plt.figure()
ax1 = rain.plot(kind="bar")
ax2 = ax1.twinx()
ax2.plot(ax1.get_xticks(),temp,linestyle='-',color="r")
ax2.set_ylim((-5, 50.))
#ax1.set_ylim((0, 300.))
ax1.set_ylabel('Precipitation (mm)', color='blue')
ax2.set_ylabel('Temperature (°C)', color='red')
ax1.set_xlabel('Months')
plt.title(location)
labels = ['Jan','Feb','Mar','Apr','May','Jun', 'Jul','Aug','Sep','Oct','Nov','Dez']
#plt.xticks(range(12),labels,rotation=45)
ax1.set_xticklabels(labels, rotation=45)  

, , :