Drop rows with certain values pandas code example

Example 1: python: remove specific values in a dataframe

df.drop(df.index[df['myvar'] == 'specific_name'], inplace = True)

Example 2: dataframe drop rows by column value

df = df[df.line_race != 0]

Example 3: pandas drop rows with value in list

import pandas as pd

a = ['2015-01-01' , '2015-02-01']

df = pd.DataFrame(data={'date':['2015-01-01' , '2015-02-01', '2015-03-01' , '2015-04-01', '2015-05-01' , '2015-06-01']})

print(df)
#         date
#0  2015-01-01
#1  2015-02-01
#2  2015-03-01
#3  2015-04-01
#4  2015-05-01
#5  2015-06-01

df = df[~df['date'].isin(a)]

print(df)
#         date
#2  2015-03-01
#3  2015-04-01
#4  2015-05-01
#5  2015-06-01

Example 4: remove all rows without a value pandas

# Keeps only rows without a missing value
df = df[df['name'].notna()]

Example 5: removing rows with specific column values from a dataframe

+---+--------------------------+----------------------------------+-----------+
| 1 | Sign up date | no_stores | no_unin_app     no_stores_recei  | ed_order  |
+---+--------------------------+----------------------------------+-----------+
| 2 | 2020-04-01   |      1    |             0                    |   0       |
| 3 | 2020-04-04   |     11    |             3                    |   6       |
| 4 | 2020-04-13   |      8    |             1                    |   4       |
+---+--------------------------+----------------------------------+-----------+