What Moves Together? in Python

Do customers who visit more also order more? Correlation answers with one number from -1 to 1. Near 1, two columns rise together. Near -1, one rises as the other falls. Near 0, there is no straight-line link.

df[cols].corr() gives back a table with the correlation of every pair of the columns in cols. Down its diagonal, each column with itself is 1.0. .loc[row, column] picks one cell. For example, on two made-up columns:

t = pd.DataFrame({"hours": [1, 2, 3, 4], "score": [50, 60, 65, 80]})
print(round(t.corr().loc["hours", "score"], 2))   # 0.98

To find the column that moves most with another, take that column of the table and .drop(label) its own row: it gives back the Series without that label. .sort_values() gives back the values in order, smallest first. .abs() drops the minus signs, because -0.6 is a stronger link than 0.5, and .idxmax() gives back the label of the biggest value. And remember: two columns that move together don't prove that one causes the other.

Your script must print:

                 visits  orders  spent  days_since_last  returned_item  bought_again
visits             1.00    0.65   0.40            -0.27           0.01          0.50
orders             0.65    1.00   0.68            -0.35          -0.05          0.49
spent              0.40    0.68   1.00            -0.28          -0.04          0.40
days_since_last   -0.27   -0.35  -0.28             1.00           0.01         -0.42
returned_item      0.01   -0.05  -0.04             0.01           1.00         -0.08
bought_again       0.50    0.49   0.40            -0.42          -0.08          1.00
visits and orders: 0.65
days_since_last   -0.42
returned_item     -0.08
spent              0.40
orders             0.49
visits             0.50
visits moves most with bought_again (0.5), but that does not show that one causes the other.

Your task: print the correlation table of six number columns and the visits-orders cell. Then print every column's correlation with bought_again, sorted, and a sentence naming the column that moves most with it, up or down.

Assignment
Follow the Coding Tutorial to build the correlation table of six columns and find the one that moves most with bought_again.

Hint
Drop bought_again's 1.0 with itself first, or it always wins. Then compare sizes with .abs() before .idxmax(): -0.42 is a stronger link than 0.40.