Seabornで学ぶデータ可視化入門
Content Team
DataCamp
関係プロットの2種類:散布図と折れ線グラフ
散布図
折れ線グラフ


import matplotlib.pyplot as plt
import seaborn as sns
sns.relplot(x="hour", y="NO_2_mean",
data=air_df_mean,
kind="scatter")
plt.show()

import matplotlib.pyplot as plt
import seaborn as sns
sns.relplot(x="hour", y="NO_2_mean",
data=air_df_mean,
kind="line")
plt.show()


import matplotlib.pyplot as plt import seaborn as sns sns.relplot(x="hour", y="NO_2_mean", data=air_df_loc_mean, kind="line", style="location", hue="location")plt.show()

import matplotlib.pyplot as plt import seaborn as sns sns.relplot(x="hour", y="NO_2_mean", data=air_df_loc_mean, kind="line", style="location", hue="location", markers=True)plt.show()

import matplotlib.pyplot as plt import seaborn as sns sns.relplot(x="hour", y="NO_2_mean", data=air_df_loc_mean, kind="line", style="location", hue="location", markers=True, dashes=False)plt.show()


import matplotlib.pyplot as plt
import seaborn as sns
sns.relplot(x="hour", y="NO_2",
data=air_df,
kind="scatter")
plt.show()

import matplotlib.pyplot as plt
import seaborn as sns
sns.relplot(x="hour", y="NO_2",
data=air_df,
kind="line")
plt.show()

影付き領域は信頼区間

import matplotlib.pyplot as plt import seaborn as sns sns.relplot(x="hour", y="NO_2", data=air_df, kind="line", errorbar="sd")plt.show()

import matplotlib.pyplot as plt import seaborn as sns sns.relplot(x="hour", y="NO_2", data=air_df, kind="line", errorbar=None)plt.show()

Seabornで学ぶデータ可視化入門