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python plots
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import pandas as pd | |
from sklearn.datasets import load_iris | |
import matplotlib.pyplot as plt | |
import seaborn as sns | |
data = pd.DataFrame(load_iris()["data"],columns=load_iris()['feature_names']) | |
data["species"] = load_iris()["target"] | |
data.head() |
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species_count = pd.Series(y).value_counts() | |
species_count['setosa'] = 30 | |
species_count['versicolor'] = 10 | |
species_count = species_count.reset_index().copy() | |
species_count.columns = ["species","count"] | |
species_count |
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fig = plt.figure(figsize=(3,5)) | |
sns.scatterplot(x=10,y=species_count['count'],size=species_count["count"],sizes=(300,2000),legend=False) | |
plt.title("Species Count") | |
plt.yticks(range(0,70,10))#setting custom y-ticks | |
plt.axis('off') #hiding the axes | |
for i in range(len(species_count)): | |
plt.text(x=9.5,y=species_count.iloc[i,1]-1,s=species_count.iloc[i,0]) | |
plt.text(x=10.2,y=species_count.iloc[i,1]-1,s=species_count.iloc[i,1]) |
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fig = plt.figure(figsize=(7,7)) | |
sns.scatterplot(x="petal width (cm)",y="sepal length (cm)",data=data,hue="species",s=70) | |
plt.grid(linestyle="--",color="gray") |
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fig = plt.figure(figsize=(7,7)) | |
sns.scatterplot(x="petal width (cm)",y="sepal length (cm)",data=data,hue="species",s=70) | |
plt.legend(loc="upper left",ncol=3,framealpha=1,fontsize=10) | |
plt.grid(linestyle="--",color="gray") |
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fig = plt.figure(figsize=(7,7)) | |
sns.scatterplot(x="petal width (cm)",y="sepal length (cm)",data=data,hue="species",s=70) | |
plt.legend(loc="upper left",ncol=3,framealpha=1,fontsize=10) | |
plt.figtext(x=0,y=0,s="* This is foot note") | |
plt.grid(linestyle="--") |
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median_data = data.groupby("species").median() | |
median_data |
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fig,ax = plt.subplots(1,4,figsize=(20,5)) | |
col = 0 | |
for n,i in enumerate(median_data.columns): | |
median_data[i].plot(kind="bar",ax=ax[col]) | |
ax[col].set_title(i) | |
col += 1 | |
plt.show() |
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X = data.iloc[:,:-1].copy() | |
y = data["species"] | |
row = col = 0 # initializing row and column counters | |
n = 0 # counter variable | |
fig,ax = plt.subplots(2,3,figsize=(20,10)) | |
for i in range(len(X.columns)-1): | |
for j in range(i+1,len(X.columns)): | |
if (n%3==0) & (n>0): | |
col = 0 | |
row += 1 | |
sns.scatterplot(x=X.columns[i],y=X.columns[j],data=X,hue=y,ax=ax[row,col],s=50) | |
ax[row,col].grid(linestyle="--") | |
col += 1 | |
n += 1 | |
plt.show() |
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fig,ax = plt.subplots(1,4,figsize=(20,5)) | |
col = 0 | |
for i in median_data.columns: | |
median_data[i].plot(kind="bar",ax=ax[col]) | |
ax[col].set_title(i) | |
for n,j in enumerate(median_data.index): | |
ax[col].text(x=n-0.1,y=median_data.loc[j,i]+0.02,s=median_data.loc[j,i]) | |
col += 1 | |
plt.show() |
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fig,ax = plt.subplots(1,4,figsize=(20,5)) | |
fig.set_facecolor("black") | |
col = 0 | |
for i in median_data.columns: | |
median_data[i].plot(kind="bar",ax=ax[col],color="white") | |
ax[col].set_title(i) | |
for n,j in enumerate(median_data.index): | |
ax[col].set_facecolor("black") | |
#changing color of axis spines | |
ax[col].spines["bottom"].set_color("white") | |
ax[col].spines["left"].set_color("white") | |
#changing x-axis label and tick colors | |
ax[col].xaxis.label.set_color("white") | |
ax[col].tick_params(axis='x', colors='white') | |
#changing y-axis label and tick colors | |
ax[col].yaxis.label.set_color("white") | |
ax[col].tick_params(axis='y', colors='white') | |
#removing x label | |
ax[col].set_xlabel("") | |
ax[col].text(x=n-0.1,y=median_data.loc[j,i]+0.02,s=median_data.loc[j,i],color="white",fontsize=12) | |
col += 1 | |
plt.show() |
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