# Print the first five rows of gold

pandas cheatsheet

How to read CSV(comma separated value files) to DF(dataframes). bronze = pd.read_csv('Bronze.csv')

You can change the order of the rows in a DataFrame by calling .sort_values(). It's also useful to be able to sort by elements in the index. For this, you need to use .sort_index().

Call .set_index(), passing the two column names as a list.

Without an index, subsetting takes the form df[df["column"].isin(values)].

reset_index(), temperatures_ind.reset_index(drop=True), temperatures.set_index("city")

In pandas, pivot tables are essentially just another way of performing grouped calculations. That is, the .pivot_table() method is just an alternative to .groupby().

Use np.min() np.max() np.mean() np.median()

var=sales.groupby("type")[["unemployment", "fuel_price_usd_per_l"]].agg([np.min, np.max, np.mean, np.me

Calculations with groupby() -> when you have two columns to group use

sales.groupby("type")["weekly_sales"].sum()

Print the dataframe and look through the columns by print(dataframe.to_string()

.value_counts()

Counting the number of each type of store and the number of each type of department. stores and departments are both DataFrames.