In pandas iloc loc take data difference and the method of value according to conditions in detail

Dataframe uses loc to fetch rows and columns:

print(df.loc[0:4,['item_price_level','item_sales_level','item_collected_level','item_pv_level']])

The results are as follows, with 5 rows and 4 columns of index 0 to 4.

  item_price_level item_sales_level item_collected_level item_pv_level
0     3     3      4    14
1     3     3      4    14
2     3     3      4    14
3     3     3      4    14
4     3     3      4    14

Instead of using iloc, it looks like this:

print(df.iloc[0:4,6:9])

The results are as follows, with index for rows 0 through 34, and 3 columns 6 through 8 (starting with column 0).

  item_price_level item_sales_level item_collected_level
0     3     3      4
1     3     3      4
2     3     3      4
3     3     3      4

In addition, loc can fetch data according to conditions:

print(df.loc[df.item_price_level==0,:])
print(df.loc[df[item_price_level]==0,:])

item_price_level = 0 item_price_level = 0 item_price_level = 0 We can change the colon to the name of several columns, and select only the columns that meet our condition:

print(df.loc[df['item_price_level']==0,['item_price_level','item_sales_level']])

The first two lines of the result are as follows:

   item_price_level item_sales_level
129141     0    10
129142     0    10

When the condition is multiple (both conditions are satisfied as follows) :

print(df.loc[(item_price_level==0) & (item_sales_level==3),:])