code session 16 Pandas.py

#!/usr/bin/env python
# coding: utf-8

# # Filter DataFrame with More than One Condition (AND - &)

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import pandas as pd


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df=pd.read_csv("employees.csv",parse_dates=["Start Date","Last Login Time"])
df["Senior Management"]=df["Senior Management"].astype("bool")
df["Gender"]=df["Gender"].astype("category")
df.head(3)


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mask=df["Gender"] == "Male"
df[mask]


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df["Team"] == "Marketing"


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mask1 = df["Gender"] == "Male"
mask2 = df["Team"] == "Marketing"


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mask1 = df["Gender"] == "Male"
df[mask1]


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df [mask1 & mask2]


# # Filter DataFrame with More than One Condition (OR - )

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df=pd.read_csv("employees.csv",parse_dates=["Start Date","Last Login Time"])
df["Senior Management"]=df["Senior Management"].astype("bool")
df["Gender"]=df["Gender"].astype("category")
df.head(3)


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mask1 = df["Senior Management"]
mask2 = df["Start Date"] < "1990-01-01"


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df[mask1 | mask2]


# In[16]:


mask1 = df["First Name"] == "Robert"
mask2 = df["Team"] == "Client Services"
mask3 = df["Start Date"] > "2016-06-01"
df[(mask1 & mask2) | mask3]


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