I am just starting to learn Pandas, and in a piece of code, there is a call to df.iloc[[1][0]] (where df is a pd.DataFrame with a shape of (60935, 54)). From the context of the code, df.iloc[[1][0]] seems to represent a row of df. However, how should one interpret [[1][0]]? Why does iloc[] allow two adjacent lists as parameters? How does iloc[] handle this parameters internally? This clearly is not indexing both rows and columns. Additionally, I noticed that when the second number is neither 0 nor -1, an index out-of-range error occurs. Why is this?

I am just starting to learn Pandas, and in a piece of code, there is a call to df.iloc[[1][0]] (where df is a pd.DataFrame with a shape of (60935, 54)). From the context of the code, df.iloc[[1][0]] seems to represent a row of df. However, how should one interpret [[1][0]]? Why does iloc[] allow two adjacent lists as parameters? How does iloc[] handle this parameters internally? This clearly is not indexing both rows and columns. Additionally, I noticed that when the second number is neither 0 nor -1, an index out-of-range error occurs. Why is this?

I am just starting to learn Pandas, and in a piece of code, there is a call to df.iloc[[1][0]] (where df is a pd.DataFrame with a shape of (60935, 54)). From the context of the code, df.iloc[[1][0]] seems to represent a row of df. However, how should one interpret [[1][0]]? Why does iloc[] allow two adjacent lists as parameters? How does iloc[] handle this parameters internally? This clearly is not indexing both rows and columns. Additionally, I noticed that when the second number is neither 0 nor -1, an index out-of-range error occurs. Why is this?

I am just starting to learn Pandas, and in a piece of code, there is a call to df.iloc[[1][0]] (where df is a pd.DataFrame with a shape of (60935, 54)). From the context of the code, df.iloc[[1][0]] seems to represent a row of df. However, how should one interpret [[1][0]]? Why does iloc[] allow two adjacent lists as parameters? How does iloc[] handle this parameters internally? This clearly is not indexing both rows and columns. Additionally, I noticed that when the second number is neither 0 nor -1, an index out-of-range error occurs. Why is this?

I am just starting to learn Pandas, and in a piece of code, there is a call to df.iloc[[1][0]] (where df is a pd.DataFrame with a shape of (60935, 54)). From the context of the code, df.iloc[[1][0]] seems to represent a row of df. However, how should one interpret [[1][0]]? Why does iloc[] allow two adjacent lists as parameters? How does iloc[] handle this parameters internally? This clearly is not indexing both rows and columns. Additionally, I noticed that when the second number is neither 0 nor -1, an index out-of-range error occurs. Why is this?