I'm having trouble creating this plot in spyder:
import seaborn as sns
import pandas as pd
from pandas.api.types import CategoricalDtype
diamonds= sns.load_dataset("diamonds")
df=diamonds.copy()
cut_Kategoriler=["Fair","Good","Very Good","Premium","Ideal"]
df.cut=df.cut.astype(CategoricalDtype(categories = cut_Kategoriler,ordered=True))
print(df.head())
sns.catplot(x="cut",y="price",data=df)
sns.barplot(x="cut",y="price",hue="color",data=df)
I want create two plots. But these plots overflap. How can i separate the graphics in the last two lines?
You need to import matplotlib.pyplot as plt and then add plt.show() after each of the two plots.
The modified code is added below:
import seaborn as sns
import pandas as pd
import matplotlib.pyplot as plt # Import Matplotlib
from pandas.api.types import CategoricalDtype
diamonds = sns.load_dataset("diamonds")
df=diamonds.copy()
cut_Kategoriler=["Fair","Good","Very Good","Premium","Ideal"]
df.cut=df.cut.astype(CategoricalDtype(categories = cut_Kategoriler,ordered=True))
print(df.head())
sns.catplot(x="cut",y="price",data=df)
plt.show() # Display the first plot
sns.barplot(x="cut",y="price",hue="color",data=df)
plt.show() # Display the second plot
Related
When rendering matplotlib charts using pyscript and using figure(figsize) the chart disappears and replaces the x and y axes. Why is this happening?
With figsize
Without figsize
import pandas as pd
import numpy as np
import matplotlib.pyplot as plt
import seaborn as sns
from pyodide.http import open_url
url = open_url('../data/salaries.csv')
df = pd.read_csv(url)
df_no_outliers=df[(df.salary_in_usd>min) & (df.salary_in_usd<max)]
top_jobs=df_no_outliers.job_title.value_counts()[:7]
plt.figure(2)
barplot = sns.barplot(x='work_year', y='salary_in_usd', data=df_no_outliers)
plt.tight_layout()
plt.figure(figsize=(15,8))
plt
Can someone help me with how to create a scatterplot. I have written the following code, however, it is not the scatter plot link that I expected as all data only concentrate 3 values of x-variable
import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
import seaborn as sns
from sklearn.linear_model import LinearRegression
from scipy.stats import skew
from warnings import filterwarnings
filterwarnings('ignore')
df_transactions = pd.read_csv('transactions.csv')
daily_revenue= df_transactions.groupby("days_after_open").sum()['revenue']
df_transactions["daily_revenue"] = daily_revenue
x = df_transactions["days_after_open"]
y = df_transactions["daily_revenue"]
plt.scatter(x,y,alpha=0.2)
plt.xlabel("Days After Open (days)")
plt.ylabel("Daily Reveue ($)")
plt.savefig("plot")
dataframe image
Please define the 'daily_revenue' following before moving to the scatter plot.
y = df_transactions["daily_revenue"]
i've got two datasets with the exact same data but they look different when plotted the same way. One is a .xlsx file and one is a .csv file.
Here are the two codes:
For the CSV:
import numpy as np
import pandas as pd
import statsmodels.api as sm
import matplotlib.pyplot as plt
import seaborn as sns
sns.set()
from sklearn.cluster import KMeans
daten = pd.read_csv(r"Path\Übungsdaten.csv", header=0, sep=";")
print("Total rows: {0}".format(len(daten)))
print(daten.columns)
plt.scatter(daten['InsuredValue'], daten['Policy'])
plt.xlim(2500000)
plt.ylim(100100)
plt.show()
And for the xlsx:
import numpy as np
import pandas as pd
import statsmodels.api as sm
import matplotlib.pyplot as plt
import seaborn as sns
sns.set()
from sklearn.cluster import KMeans
daten = pd.read_excel(r"Path\Übungsdaten.xlsx")
print("Total rows: {0}".format(len(daten)))
plt.scatter(daten['InsuredValue'],daten['Policy'] )
plt.xlim(2500000)
plt.ylim(100100)
plt.show()
Here are the two Plots:
csv with plt.xlim(2500000) plt.ylim(100100)
and the csv without restrictions:
and finally the .xlsx plot:
My question is first of all, why is there a black bar on the bottom of the first two plots? (im guessing this is every single value of "InsuredValue") and how can I form the csv plo to the same ratio as the xlsx plot?
Thank you very much
I had to convert the "InsuredValue" column to int with the following code:
daten.astype({'InsuredValue':'int'})
I have a scatter plot im working with and for some reason im not seeing all the x values on my graph
#%%
from pandas import DataFrame, read_csv
import pandas as pd
import matplotlib.pyplot as plt
import seaborn as sns
file = r"re2.csv"
df = pd.read_csv(file)
#sns.set(rc={'figure.figsize':(11.7,8.27)})
g = sns.FacetGrid(df, col='city')
g.map(plt.scatter, 'type', 'price').add_legend()
This is an image of a small subset of my plots, you can see that Res is displaying, the middle bar should be displaying Con and the last would be Mlt. These are all defined in the type column from my data set but are not displaying.
Any clue how to fix?
Python is doing what you tell it to do. Just pick different features, presumably things that make more sense for plotting, if you want to generate a more interesting plots. See this generic example below.
import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
import seaborn as sns
sns.set_theme(style="darkgrid")
tips = sns.load_dataset("tips")
sns.relplot(x="total_bill", y="tip", hue="smoker", data=tips);
Personally, I like plotly plots, which are dynamic, more than I like seaborn plots.
https://plotly.com/python/line-and-scatter/
I want to fill the area under a line plot so it looks as the picture below:
instead of
built on the following .csv file:
01-01-97 1
01-02-97 2
01-03-97 3
...
01-11-17 251
01-12-17 252
01-01-18 253
what should I change in this code to generate the desired graph?
import pandas as pd
import seaborn as sns
from matplotlib import pyplot as plt
# load csv
df=pd.read_csv("test.csv")
# generate graph
g = sns.lineplot(x="Date", y="Data", data=df)
plt.show()
plt.fill_between(df.Date.values, df.Data.values)
Here's an alternative, using a stacked line chart:
import pandas as pd
import seaborn as sns
from matplotlib import pyplot as plt
# load csv
df = pd.read_csv("test.csv")
# generate graph
plt.stackplot(df["Date"], df["Data"], alpha=0.5)
plt.show()