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import pandas as pd # read data df = pd.read_csv("/path/to/file.csv") # alternative: read from excel df = pd.read_csv("/path/to/file.xlsx", sheet_name="sheet name") # sanity check: view the dataframe df.info()import pandas as pd # read data df = pd.read_csv("/path/to/file.csv") # alternative: read from excel df = pd.read_csv("/path/to/file.xlsx", sheet_name="sheet name") # sanity check: view the dataframe df.info()import pandas as pd # read data df = pd.read_csv("/path/to/file.csv") # alternative: read from excel df = pd.read_csv("/path/to/file.xlsx", sheet_name="sheet name") # sanity check: view the dataframe df.info()
from ydata_profiling import ProfileReport # in a jupyter notebook cell ProfileReport(df) # to use jupyter widgets report = ProfileReport(df) report.to_widgets() # to save to disk report.to_file("/path/to/report.html")from ydata_profiling import ProfileReport # in a jupyter notebook cell ProfileReport(df) # to use jupyter widgets report = ProfileReport(df) report.to_widgets() # to save to disk report.to_file("/path/to/report.html")from ydata_profiling import ProfileReport # in a jupyter notebook cell ProfileReport(df) # to use jupyter widgets report = ProfileReport(df) report.to_widgets() # to save to disk report.to_file("/path/to/report.html")
import seaborn as sns # simplest way sns.histplot(data=df, x="variable") # preferred way import matplotlib.pyplot as plt fig, ax = plt.subplots() sns.histplot(data=df, x="variable", ax=ax) plt.show()import seaborn as sns # simplest way sns.histplot(data=df, x="variable") # preferred way import matplotlib.pyplot as plt fig, ax = plt.subplots() sns.histplot(data=df, x="variable", ax=ax) plt.show()
import seaborn as sns # simplest way sns.boxplot(data=df, x="variable") # preferred way import matplotlib.pyplot as plt fig, ax = plt.subplots() sns.boxplot(data=df, x="variable", ax=ax) plt.show()import seaborn as sns # simplest way sns.boxplot(data=df, x="variable") # preferred way import matplotlib.pyplot as plt fig, ax = plt.subplots() sns.boxplot(data=df, x="variable", ax=ax) plt.show()
import seaborn as sns # simplest way sns.scatterplot(data=df, x="independent_variable", y="dependent_variable") # preferred way import matplotlib.pyplot as plt fig, ax = plt.subplots() sns.scatterplot(data=df, x="independent_variable", y="dependent_variable", ax=ax) plt.show()import seaborn as sns # simplest way sns.scatterplot(data=df, x="independent_variable", y="dependent_variable") # preferred way import matplotlib.pyplot as plt fig, ax = plt.subplots() sns.scatterplot(data=df, x="independent_variable", y="dependent_variable", ax=ax) plt.show()
import seaborn as sns # simplest way sns.lineplot(data=df, x="independent_variable", y="dependent_variable") # preferred way import matplotlib.pyplot as plt fig, ax = plt.subplots() sns.lineplot(data=df, x="independent_variable", y="dependent_variable", ax=ax) plt.show()import seaborn as sns # simplest way sns.lineplot(data=df, x="independent_variable", y="dependent_variable") # preferred way import matplotlib.pyplot as plt fig, ax = plt.subplots() sns.lineplot(data=df, x="independent_variable", y="dependent_variable", ax=ax) plt.show()
import seaborn as sns # simplest way sns.barplot(data=df, x="independent_variable", y="dependent_variable") # preferred way import matplotlib.pyplot as plt fig, ax = plt.subplots() sns.barplot(data=df, x="independent_variable", y="dependent_variable", ax=ax) plt.show()import seaborn as sns # simplest way sns.barplot(data=df, x="independent_variable", y="dependent_variable") # preferred way import matplotlib.pyplot as plt fig, ax = plt.subplots() sns.barplot(data=df, x="independent_variable", y="dependent_variable", ax=ax) plt.show()
Tip
Check the seaborn and matplotlib galleries for inspiration on creating outstanding plots