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Format y axis as percent
(10 answers)
Closed 2 years ago.
I am just wondering, how do I add a percentage (%) symbol after each value in my plot along the X axis, not converting the values to a percentage?
For example: Say I have the values 5, 10, 15, 20... How would I make them appear as 5%, 10%, 15%, 20% etc., along the X axis, but not converting them to 0.05%, 0.1%, 0.15%, 0.2% etc.
Code for my plot:
import pandas as pd
import numpy as np
import matplotlib.pyplot as plt
%matplotlib inline
import seaborn as sns
sns.set(
What needs to be added to my plot code to make the percentage (%) symbol appear after each value in my X axis?
sns.displot(data=df, x="column_name", kde=True)
PercentFormatter() should work for you as shown in the working example below:
import seaborn as sns
import numpy as np
import matplotlib.ticker as mtick
import matplotlib.pyplot as plt
np.random.seed(0)
x = np.random.randn(100)
fig, ax = plt.subplots(figsize=(16,8))
sns.distplot(x, vertical=True)
Then, at the end do:
ax.xaxis.set_major_formatter(mtick.PercentFormatter())
Related
I have an Excell file and I want to plot all values higher than 200000 (for example) in the column Verkaufspreis
#Calling the Excell file
import pandas as pd
df = pd.read_excel("wohnungspreise.xlsx")
#ploting the date in a table
%matplotlib inline
import matplotlib.pyplot as plt
plt.scatter(df["Quadratmeter"], df["Verkaufspreis"])
if(df["Verkaufspreis"] > 200000){
plt.show()
}
I would like to ask question regarding to barplot for seaborn.
I have a dataset returned from bigquery and converted to dataframe as below.
Sample data from `df.sort_values(by=['dep_delay_in_minutes']).to_csv(csv_file)`
,dep_delay_in_minutes,arrival_delay_in_minutes,numflights
1,-50.0,-38.0,2
2,-49.0,-59.5,4
3,-46.0,-28.5,4
4,-45.0,-44.0,4
5,-43.0,-53.0,4
6,-42.0,-35.0,6
7,-40.0,-26.0,4
8,-39.0,-33.5,4
9,-38.0,-21.5,4
10,-37.0,-37.666666666666664,12
11,-36.0,-35.0,2
12,-35.0,-32.57142857142857,14
13,-34.0,-30.0,18
14,-33.0,-26.200000000000003,10
15,-32.0,-34.8,10
16,-31.0,-28.769230769230766,26
17,-30.0,-34.93749999999999,32
18,-29.0,-31.375000000000004,48
19,-28.0,-24.857142857142854,70
20,-27.0,-28.837209302325583,86
I wrote the code as below but the negative value is plotted on right hand side .
import matplotlib.pyplot as plt
import seaborn as sb
import pandas as pd
import numpy as np
import google.datalab.bigquery as bq
import warnings
# Disable warnings
warnings.filterwarnings('ignore')
sql="""
SELECT
DEP_DELAY as dep_delay_in_minutes,
AVG(ARR_DELAY) AS arrival_delay_in_minutes,
COUNT(ARR_DELAY) AS numflights
FROM flights.simevents
GROUP BY DEP_DELAY
ORDER BY DEP_DELAY
"""
df = bq.Query(sql).execute().result().to_dataframe()
df = df.sort_values(['dep_delay_in_minutes'])
ax = sb.barplot(data=df, x='dep_delay_in_minutes', y='numflights', order=df['dep_delay_in_minutes'])
ax.set_xlim(-50, 0)
How can I display x axis as numeric order with negative values on left hand side ?
I appreciate if I could get some adice.
It doesn't work to specify left and right with ax.set_xlim(). It was displayed well with only one specification.
import matplotlib.pyplot as plt
import seaborn as sb
import pandas as pd
import numpy as np
df = df.sort_values(['dep_delay_in_minutes'])
ax = sb.barplot(x='dep_delay_in_minutes', y='numflights', data=df, order=df['dep_delay_in_minutes'])
ax.set_xlim(0.0)
labels = ax.get_xticklabels()
plt.setp(labels, rotation=45)
plt.show()
A different notation was also possible.
ax.set_xlim(0.0,)
My DataFrame's structure
trx.columns
Index(['dest', 'orig', 'timestamp', 'transcode', 'amount'], dtype='object')
I'm trying to plot transcode (transaction code) against amount to see the how much money is spent per transaction. I made sure to convert transcode to a categorical type as seen below.
trx['transcode']
...
Name: transcode, Length: 21893, dtype: category
Categories (3, int64): [1, 17, 99]
The result I get from doing plt.scatter(trx['transcode'], trx['amount']) is
Scatter plot
While the above plot is not entirely wrong, I would like the X axis to contain just the three possible values of transcode [1, 17, 99] instead of the entire [1, 100] range.
Thanks!
In matplotlib 2.1 you can plot categorical variables by using strings. I.e. if you provide the column for the x values as string, it will recognize them as categories.
import pandas as pd
import numpy as np
import matplotlib.pyplot as plt
df = pd.DataFrame({"x" : np.random.choice([1,17,99], size=100),
"y" : np.random.rand(100)*100})
plt.scatter(df["x"].astype(str), df["y"])
plt.margins(x=0.5)
plt.show()
In order to optain the same in matplotlib <=2.0 one would plot against some index instead.
import pandas as pd
import numpy as np
import matplotlib.pyplot as plt
df = pd.DataFrame({"x" : np.random.choice([1,17,99], size=100),
"y" : np.random.rand(100)*100})
u, inv = np.unique(df["x"], return_inverse=True)
plt.scatter(inv, df["y"])
plt.xticks(range(len(u)),u)
plt.margins(x=0.5)
plt.show()
The same plot can be obtained using seaborn's stripplot:
sns.stripplot(x="x", y="y", data=df)
And a potentially nicer representation can be done via seaborn's swarmplot:
sns.swarmplot(x="x", y="y", data=df)
I'm new in matplotlib, and I want change the value's format of the axis x, like this:
Axis x : 250000, 500000, etc. Change to the format 0.250, 0.500, etc.
What can I do for this point?
Thanks
You would usually just scale the data prior to plotting. So instead of plt.plot(x,y), you'd use plt.plot(x,y/1e6).
To format the values with 3 decimal places, use a matplotlib.ticker.StrMethodFormatter and supply a format with 3 decimals, in this case "{x:.3f}".
import matplotlib.pyplot as plt
import matplotlib.ticker
import numpy as np; np.random.seed(42)
x = np.arange(5)
y = np.array([5e5,2e5,0,3e5,4e5])
plt.plot(x,y/1e6)
plt.gca().yaxis.set_major_formatter(matplotlib.ticker.StrMethodFormatter("{x:.3f}"))
plt.show()
I have the following code that shows the following plot. I can't get to show the fiscal year correctly on the x axis and it's showing as if they are float. I tried to do the astype(int) and it didn't work. Any ideas on what I am doing wrong?
p1 = plt.bar(list(asset['FISCAL_YEAR']),list(asset['TOTAL']),align='center')
plt.show()
This is the plot:
In order to make sure only integer locations obtain a ticklabel, you may use a matplotlib.ticker.MultipleLocator with an integer number as argument.
To then format the numbers on the axes, you may use a matplotlib.ticker.StrMethodFormatter.
import pandas as pd
import numpy as np
import matplotlib.pyplot as plt
import matplotlib.ticker
df = pd.DataFrame({"FISCAL_YEAR" : np.arange(2000,2017),
'TOTAL' : np.random.rand(17)})
plt.bar(df['FISCAL_YEAR'],df['TOTAL'],align='center')
locator = matplotlib.ticker.MultipleLocator(2)
plt.gca().xaxis.set_major_locator(locator)
formatter = matplotlib.ticker.StrMethodFormatter("{x:.0f}")
plt.gca().xaxis.set_major_formatter(formatter)
plt.show()