Develop Reference

Unable to change color of plotted lines on matplotlib

Referred to this SO post here: Matplotlib set_color_cycle versus set_prop_cycle
But I was unable to set all 20 lines' colors to be different, picture of the graph here:
Here is my code:
import matplotlib as mpl
import matplotlib.pyplot as plt
import seaborn as sns
import numpy as np
import pandas as pd
from cycler import cycler
df = pd.read_csv(r'data.csv', index_col="Date", parse_dates=True)
df.rolling(window=30).max()[30:].head(20)
ax = df.plot()
ax.set(title='Qingdao Port', ylabel='Monthly Average Prices')
ax.set_prop_cycle('color',plt.cm.jet(np.linspace(0,1,20)))
plt.show()
Do help me out here!

User DavidG has helped me with the issue, for future reference the updated code will be included here:
import matplotlib as mpl
import matplotlib.pyplot as plt
import seaborn as sns
import numpy as np
import pandas as pd
from cycler import cycler
fig, ax = plt.subplots()
ax.set_prop_cycle('color',plt.cm.tab20(np.linspace(0,1,20)))
df = pd.read_csv(r'data.csv', index_col="Date", parse_dates=True)
df.rolling(window=30).max()[30:].head(20)
df.plot(ax=ax)
ax.set(title='Qingdao Port', ylabel='Monthly Average Prices')
plt.show()

Axis not displaying in Matplotlib

import matplotlib.pyplot as plt
import pandas as pd
import pylab as pl
import numpy as np
%matplotlib inline
!wget -O FuelConsumption.csv https://s3-api.us-geo.objectstorage.softlayer.net/cf-courses-
data/CognitiveClass/ML0101ENv3/labs/FuelConsumptionCo2.csv
df = pd.read_csv("FuelConsumption.csv")
df.head()
df1 = df[['ENGINESIZE','CYLINDERS','FUELCONSUMPTION_COMB','CO2EMISSIONS']]
df1.head(9)
plt.scatter(df1.ENGINESIZE , df1.CO2EMISSIONS , color = "black")
plt.xlabel=("enginesize")
plt.ylabel=("emission")
plt.show()
when i try to run this code i get scatter graph without axis label.
how can i get axis label if anyone can assist me ?

You need to pass the label names to xlabel and ylabel.
If it's throwing error - TypeError: 'str' object is not callable then restart the ipython kernel
import matplotlib.pyplot as plt
import pandas as pd
import pylab as pl
import numpy as np
%matplotlib inline
df = pd.read_csv("FuelConsumption.csv")
df.head()
df1 = df[['ENGINESIZE','CYLINDERS','FUELCONSUMPTION_COMB','CO2EMISSIONS']]
df1.head(9)
plt.scatter(df1.ENGINESIZE , df1.CO2EMISSIONS , color = "black")
plt.xlabel("enginesize")
plt.ylabel("emission")
plt.show()

Jupyter widgets clear_output() does not work

I was using the ipywidgets dropdown to create plots for the columns listed in the dropdown. I have two issues. Would any one help?
I used the clear_ouput() to clear out the graph before the next selection. But it did not work;
When I first time clicked the first item in the dropdown list ("quarter"), it did not response (No graph showed). I have to select other items first before I can generate the graph for "quarter".
Thanks a lot!
import pandas as pd
import numpy as np
import seaborn as sns
import matplotlib.pyplot as plt
import ipywidgets as ipw
url = "https://data.london.gov.uk/download/number-international-visitors-london/b1e0f953-4c8a-4b45-95f5-e0d143d5641e/international-visitors-london-raw.csv"
df_london = pd.read_csv(url)
dropdown_Col = ipw.Dropdown(options = ['quarter', 'market', 'dur_stay', 'mode'], description='Sel Col NM:')
output = ipw.Output()
def Col_Sel(ColNm):
output.clear_output()
with output:
sns.set_style("whitegrid")
sns.relplot(x=ColNm, y='visits', data=df_london, kind='line', ci=None)
def dropdown_Col_eventhandler(change):
Col_Sel(change.new)
dropdown_Col.observe(dropdown_Col_eventhandler, names='value')
display(dropdown_Col)
display(output)

I added plt.show() and now The clear_output works.
import pandas as pd
import numpy as np
import seaborn as sns
import matplotlib.pyplot as plt
import ipywidgets as ipw
url = "https://data.london.gov.uk/download/number-international-visitors-london/b1e0f953-4c8a-4b45-95f5-e0d143d5641e/international-visitors-london-raw.csv"
df_london = pd.read_csv(url)
dropdown_Col = ipw.Dropdown(options = ['quarter', 'market', 'dur_stay', 'mode'], description='Sel Col NM:')
output = ipw.Output()
def Col_Sel(ColNm):
output.clear_output()
with output:
sns.set_style("whitegrid")
sns.relplot(x=ColNm, y='visits', data=df_london, kind='line', ci=None)
def dropdown_Col_eventhandler(change):
Col_Sel(change.new)
dropdown_Col.observe(dropdown_Col_eventhandler, names='value')
display(dropdown_Col)
display(output)

factorplot with seaborn python

I try to plot a factorplot with seaborn
Here is my python code :
import numpy as np
import matplotlib.pyplot as plt
import matplotlib.dates as mdates
from matplotlib import style
import pandas as pd
import seaborn as sns
import io
style.use('ggplot')
#load dataset into df2 dataframe
df2 = pd.read_csv('C:/Users/Demonstrator/Downloads/power.csv',delimiter=';')
#drop NaN rows from df2 to build df_no_missing
df_no_missing = df2.dropna().copy()
df_no_missing.head()
df_no_missing['depassement'] = np.where((df_no_missing['P_ACT_KW'] - df_no_missing['P_SOUSCR']) < 0, 0, df_no_missing['P_ACT_KW'] - df_no_missing['P_SOUSCR'])
#build a factorplot
sns.factorplot(data=df_no_missing, x="TIMESTAMP", y="P_ACT_KW")
It is impossible to view a result the process seems busy.

How to create box plot from pandas object using matplotlib?

I read data into pandas object and then I want to create a box plot using matplotlib (not pandas.boxplot()). This is just for learning purposes. This is my code, in which myData['MyColumn'] fails.
import matplotlib.pyplot as plt
import pandas as pd
myData = pd.read_csv('data/myData.csv')
plt.boxplot(myData['MyColumn'])
plt.show()

Your code works fine with fake data. Check the type of the data you're trying to plot.
import matplotlib.pyplot as plt
import pandas as pd
import numpy as np
myData = pd.DataFrame(np.random.rand(10, 2), columns=['MyColumn', 'blah'])
plt.boxplot(myData['MyColumn'])
plt.show()