Pandas

Question 1

How to define your data frame from a csv file that is sitting in the same folder as your Python file?

Answer 1

df = pd.read_csv(“finename.csv”)

Question 2

How to display the first 5 rows of your dataframe?

Answer 2

df.head(5)

Question 3

How to display the last 5 rows of your dataframe?

Answer 3

df.tail(5)

Question 4

How to save a dataframe to a specific format?

Answer 4

df.to_filetype(filename)

Question 5

How to get the number of rows and columns of a dataframe?

Answer 5

df.shape

Question 6

How to get the index, datatype and memory information of a dataframe?

Answer 6

df.info()

Question 7

How to return a Series containing counts of unique values?

Answer 7

Series.value_counts()

Question 8

How to generate descriptive statistics from a dataframe? (Descriptive statistics include those that summarize the central tendency, dispersion and shape of a dataset’s distribution, excluding NaN values)

Answer 8

df.describe()
df[‘column_name’].describe()

Question 9

How to check data type?

Answer 9

df.dtypes

Question 10

Ho to change data type?

Answer 10

astype()
Ex: astype(str) -> will tranform into a string

Question 11

How to check missing value?

Answer 11

df.isnull().sum()
OR
df[df[‘column_name’].isnull()]

Question 12

How to assign to a variable the content of a specific column?

Answer 12

df1 = df[“column_name”]

Question 13

How to assign to a variable the content of several columns?

Answer 13

df1 = df[[“column_name1”, “column_name2”]]

Question 14

How to delete column?

Answer 14

del df[“column_name”]

Question 15

How to check the content of one column that is above a certain number?

Answer 15

df1 = df [(df [“column_name”] > 1500 ) ]
print df1

Question 16

What is the argument “index_col” of the pandas read_csv function used for?

Answer 16

You can specify which column to use as the left index for the rows.
df1 = pd.read_csv(“ToshlExpenses - Toshl Dépenses.csv”, index_col=”Expense\nin Euro”)
df1

Question 17

How to replace Null values in dataframe?

Answer 17

df.fillna()

Question 18

How to analyze a dataframe and drop Rows/Columns with Null values?

Answer 18

df.dropna()