Data Analysis with Python Week 3 Exploratory Data Analysis

Use describe() for objects

df.describe(include=['object'])

Find the correlation between several columns

df[['col_A', 'col_B', 'col_C', 'col_D']].corr()

A dataframe, df_NHL_players has a categorical column named 'position'. Get the number of players in each position

position_cnts = df_NHL_players['position'].value_counts()

Make boxplots for all in a particular category

sns.boxplot(x="col_category", y="col_quantity", data=df)

Install seaborn

%%capture ! pip install seaborn import seaborn as sns

Plot values from one column on the vertical axis and another column on the horizontal axis. The lower limit the vertical axis should be zero.

sns.regplot(x="engine-size", y="price", data=df) plt.ylim(0,)

A dataframe, df_NHL_players has a categorical column named 'position'. Get the number of players in each position and then cast those numbers into a dataframe

position_cnts = df_NHL_players['position'].value_counts() df_position_cnts = position_cnts.to_frame()

Plot values from one column on the vertical axis and another column on the horizontal axis

sns.regplot(x="col_A", y="col_B", data=df)