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Manipulate data

Perform novel analysis on your data.
Manipulating data in Quadratic is easier than ever as you can view your changes in the sheet in real-time. Here is a non-exhaustive list of ways to manipulate your data in Quadratic:

1. Find correlations

Get your correlation and show that value in the sheet.
// correlation between two columns
data['col1'].corr(data['col2'], method='pearson')
// possible methods: pearson, kendall, spearman

2. Basic stats - max, min, mean, selections, etc.

// max from column
df["col1"].max()
// min from column
df["col1"].min()
// mean from column
df["col1"].mean()
// median from column
df["col1"].median()
// skew for all columns
df.skew()
// count values in the column
df["col1"].value_counts()
// summary of column
df["col1"].describe()

3. DataFrame math

Do math on data in the DataFrame. Alternatively, use formulas in the sheet on the values in the sheet.
// add, subtract, multiply, etc. - will work on all values in column
df['col1'] + 1
df['col1'] * 2
df['col1'] / 2
// do any arbitrary math column-wise with the above or just do DataFrame-wise via
df + 1

4. Data selections

Alternatively, cut/copy/paste specific values in the sheet.
// get a column
df['col1']
// get multiple columns
df[['col1', 'col2']]
// filtering

5. Prep for visualizations

Visualizations are in active development.

6. POST your data to external APIs

This is a feature in active development for better CORS requests.