sample code:
import pandas as pd
import numpy as np
sample = pd.DataFrame({"a":[1,2,3,1,2,3,1,2,3], "b":np.random.uniform(0,1,9)})
sample.boxplot(column="b", by=pd.cut(sample.a, bins=2))
Apart from the box plot picture, some text appears around the plot. How can I remove the text from the plot?
You can try create new column c by cut, because in DataFrame.boxplot parameter by can be column:
by : string or sequence
Column in the DataFrame to group by
import pandas as pd
import numpy as np
sample = pd.DataFrame({"a":[1,2,3,1,2,3,1,2,3], "b":np.random.uniform(0,1,9)})
sample['c'] = pd.cut(sample.a, bins=2)
sample.boxplot(column="b", by='c')
Related
Hello I cannot understand why this code does not select rows between dates. It shows me same dataset from first date 2004. Here is my code below:
import pandas as pd
from pandas import DataFrame
import datetime
from matplotlib import pyplot as plt
df1 = pd.read_csv('time_series_15min_singleindex.csv',header=0,index_col=0,parse_dates=True)
df=DataFrame(df1,columns['utc_timestamp','DE_solar_generation_actual','DE_wind_onshore_generation_actual']
df['utc_timestamp'] = pd.to_datetime(df['utc_timestamp'],utc=True)
start_date=pd.to_datetime('2008-12-31',utc=True)
end_date=pd.to_datetime('2009-01-01',utc=True)
df[df['utc_timestamp'].between(start_date,end_date)]
df.plot()
You forget assign back, use:
df = df[df['utc_timestamp'].between(start_date,end_date)]
I am trying to make a Box and Whisker plot on my dataset that looks something like this -
& the chart I'm trying to make
My current lines of code are below -
import seaborn as sns
import matplotlib.pyplot as plt
d = df3.boxplot(column = ['Northern California','New York','Kansas','Texas'], by = 'Banner')
d
Thank you
I've recreated a dummy version of your dataset:
import numpy as np
import pandas as pd
dictionary = {'Banner':['Type1']*10+['Type2']*10,
'Northen_californina':np.random.rand(20),
'Texas':np.random.rand(20)}
df = pd.DataFrame(dictionary)
What you need is to melt your dataframe (unpivot) in orther to have the information of geographical zone stored in a column and not as column name. You can use pandas.melt method and specify all the columns you want to put in your boxplot in the value_vars argument.
With my dummy dataset you can do this:
df = pd.melt(df,id_vars=['Banner'],value_vars=['Northen_californina','Texas'],
var_name='zone', value_name='amount')
Now you can apply a boxplot using the hue argument:
import seaborn as sns
import matplotlib.pyplot as plt
plt.figure(figsize=(9,9)) #for a bigger image
sns.boxplot(x="Banner", y="amount", hue="zone", data=df, palette="Set1")
This is a very straightforward question. I have and x axis of years and a y axis of numbers increasing linearly by 100. When plotting this with pandas and matplotlib I am given a graph that does not represent the data whatsoever. I need some help to figure this out because it is such a small amount of code:
The CSV is as follows:
A,B
2012,100
2013,200
2014,300
2015,400
2016,500
2017,600
2018,700
2012,800
2013,900
2014,1000
2015,1100
2016,1200
2017,1300
2018,1400
The Code:
import matplotlib.pyplot as plt
import numpy as np
import pandas as pd
data = pd.read_csv("CSV/DSNY.csv")
data.set_index("A", inplace=True)
data.plot()
plt.show()
The graph this yields is:
It is clearly very inconsistent with the data - any suggestions?
The default behaviour of matplotlib/pandas is to draw a line between successive data points, and not to mark each data point with a symbol.
Fix: change data.plot() to data.plot(style='o'), or df.plot(marker='o', linewidth=0).
Result:
All you need is sort A before plotting.
import matplotlib.pyplot as plt
import numpy as np
import pandas as pd
data = pd.read_csv("CSV/DSNY.csv").reset_index()
data = data.sort_values('A')
data.set_index("A", inplace=True)
data.plot()
plt.show()
i want to convert that dataframe
into this dataframe and plot a matplotlib graph using date along x axis
changed dataframe
Use df.T.plot(kind='bar'):
import pandas as pd
import matplotlib.pyplot as plt
df = pd.DataFrame.from_csv('./housing_price_index_2010-11_100.csv')
df.T.plot(kind='bar')
plt.show()
you can also assign the transpose to a new variable and plot that (what you asked in the comment):
import pandas as pd
import matplotlib.pyplot as plt
df = pd.DataFrame.from_csv('./housing_price_index_2010-11_100.csv')
df_transposed = df.T
df_transposed.plot(kind='bar')
plt.show()
both result the same:
Hi all so I'm trying to work with this set of data that has two columns, one is names and the other is the number of births for each name. What I want to do is import a csv file, perform some basic functions on it such as finding the baby name with the maximum number of births, and then plotting the data in a bar graph. But, when I have an index value for the dataframe, the bar graph prints that as the x axis instead of the names. So I removed the index and now I get all kinds of errors. Below is my code, first the one with the index and then the one without. Thanks in advance. This is really driving me crazy
import pandas as pd
import matplotlib.pyplot as plt
import pdb
import matplotlib as p
import os
from pandas import DataFrame
Location = os.path.join(os.path.sep,'Users', 'Mark\'s Computer','Desktop','projects','data','births1880.csv')
a = pd.read_csv(Location, index_col = False)
print(a) #print the dataframe just to see what I'm getting.
MaxValue = a['Births'].max()
MaxName = a['Names'][a['Births'] == MaxValue].values
print(MaxValue, ' ', MaxName)
a.plot(kind ='bar')
plt.show()
This code works but spits out a bar graph with the index as the x axis instead of the names?
import pandas as pd
import matplotlib.pyplot as plt
import pdb
import matplotlib as p
import os
from pandas import DataFrame
Location = os.path.join(os.path.sep,'Users', 'Mark\'s Computer','Desktop','projects','data','births1880.csv')
a = pd.read_csv(Location, index_col = True) #why is setting the index column to true removing it?
print(a) #print the dataframe just to see what I'm getting.
MaxValue = a['Births'].max()
MaxName = a['Names'][a['Births'] == MaxValue].values
print(MaxValue, ' ', MaxName)
a.plot(kind ='bar', x='Names', y = 'Births' )
plt.show()
edited for solution.
It would be nice if you'd provided a sample csv file, so I made one up, took me a while to figure out what format pandas expects.
I used a test.csv that looked like:
names,briths
mike,3
mark,4
Then my python code:
import pandas
import numpy
import matplotlib.pyplot as plt
a = pandas.read_csv('test.csv', index_col = False)
a.plot(kind='bar')
indices = numpy.arange(len(a['names']))
plt.xticks( indices+0.5, a['names'].values)
plt.show()